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IBMSPSSMPRO - IBM SPSS Modeler Professional(R) Certification - Dump Information

Vendor : IBM
Exam Code : IBMSPSSMPRO
Exam Name : IBM SPSS Modeler Professional(R) Certification
Questions and Answers : 73 Q & A
Updated On : October 18, 2018
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IBMSPSSMPRO IBM SPSS Modeler Professional(R) Certification

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IBMSPSSMPRO exam Dumps Source : IBM SPSS Modeler Professional(R) Certification

Test Code : IBMSPSSMPRO
Test Name : IBM SPSS Modeler Professional(R) Certification
Vendor Name : IBM
Q&A : 73 Real Questions

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The Drum Digerati 2018 printed: meet probably the most striking people in UK organizations | killexams.com Real Questions and Pass4sure dumps

during this week, we may be revealing who has made it into The Drum Digerati – our annual get together of one hundred remarkable people excelling in the UK digital trade. be certain you do not miss out by using signing up to our newsletter.

The Drum's Digerati showcases success and ingenuity from one of the crucial most pioneering digital entrepreneurs working within the UK these days. according to nominations from our readers and curated through our editorial team, the listing celebrates ability from four categories: corporations, manufacturers, adtech & martech and media & platforms.

today we start with the aid of profiling the 25 individuals who've made it into The Digerati from companies.

Abbie Walsh, managing director, Fjord

Abbie Walsh is a provider design pioneer, former journalist and DJ. At Fjord and Accenture, Walsh oversees Fjord's activities within the UK and eire, main key valued clientele through their digital transformation journeys and pleasing a global and regional remit to mentor leaders. within the ultimate year, she and the Fjord London crew have moved into a new studio in conjunction with Accenture Interactive. Designed in partnership with Studio Jenny Jones, the brand new space has been designed to permit creativity to thrive, bringing together distinctive partners and shoppers to create superb experiences. This year, she served as a panellist for D&ad New Blood Academy, became a juror at the Cannes Lions on the primary ever trade craft jury, and became also a juror for the D&advert Awards 2018.

Ajaz Ahmed, chief executive officer, AKQA

Ajaz Ahmed is now in his 18th yr as chief executive of AKQA, the innovation powerhouse he founded after falling by the wayside of school aged 21. This summer time marked the subsequent step in Ahmed’s vision for the company as it got a majority stake in structure and indoors design observe widespread Design Studio and industrial design consultancy Map undertaking workplace to turn it into a new multidisciplinary design group. From its roots in London, AKQA has grown to nowadays make use of round 2,100 authorities in 23 studios across the US, Latin the usa, Europe and Asia-Pacific.

Anatoly Roytman, head of Accenture Interactive EALA

As head of Europe, Africa and Latin america for Accenture Interactive, and the company’s international commerce lead, Anatoly Roytman is on a mission to create the company of the long run. during Roytman’s time at Accenture, the company has been joined by using corporations like Fjord, Karmarama and Rothco, assisting to form end-to-end capabilities and a greater artistic-led tradition, as neatly pushing Accenture into new areas of content, media and creativity. The enterprise gained its first ever Cannes Lions this 12 months, together with a Grand Prix. before becoming a member of Accenture Interactive, Roytman changed into vice-president of advertising and marketing strategy and analysis at Sapient.

Ete Davies, managing director, AnalogFolk

Appointed as managing director in 2016, Ete Davies has led AnalogFolk towards a duration of extraordinary increase and artistic excellence. inventive and commercial success has accompanied new business wins throughout Unilever, Pepsi, Nike, Nando's, BT, Danone and Scotch&Soda. far from AnalogFolk, Davies is a number one protagonist in riding range, inclusion and equality across the artistic industries, notably for the BAME neighborhood. He became one of the normal co-founders of WeAreStripes, is the founding father of CultureHeroes and sits on the advisory boards of a number of other diversity initiatives.

Fiona Proudler, chief government officer, AmazeRealise

Fiona Proudler's profession spans more than 25 years in the business. In 2017, Proudler became appointed chief executive officer of fellow kinfolk + Carta stablemate Amaze and lead the successful integration of the two groups to form AmazeRealise. Proudler oversaw the profitable of vital new manufacturers during the remaining three hundred and sixty five days together with a tremendously prestigious venture in the financial services sector calling upon the collective capabilities of the relations + Carta community. beneath her stewardship, AmazeRealise has launched a bold new positioning and is breaking ground within the US. Proudler situated the Voice of the customer strategic platform to signify the complex experiences of modern customers within a all of a sudden evolving marketplace.

James Harris, world chief method officer, Mindshare

a true veteran with over 25 years within the advertising and media world, James Harris has been a pioneer of digital promoting from its earliest days. during his career has established a number of extremely a hit media businesses, including the Media company North, now part of the global media agency network Mediacom and Diffiniti now iProspect. He has lately joined Mindshare as its world chief method officer and earlier than that he was chief digital and facts officer for Carat, the place as a member of the global govt team he helped power the building of the network's digital capabilities and strategy and helping propel in Carat being ranked the number one company through Recma – a spot it then held always.

James Hilton, world chief govt officer, M&C Saatchi efficiency

James Hilton is founder and international chief government officer of M&C Saatchi performance. upset with the lack of exceptional and advertising abilities he encountered when looking for a cell advertising and marketing supplier, Hilton made the choice to discovered his own enterprise inner mobile in early 2006. In 2018 the company repositioned as M&C Saatchi performance and is now probably the most biggest global efficiency marketing groups. apart from successful The Drum DADI's 'Digital company of the year' in 2016 and The MOMA's 'Most valuable cell company' consecutively in 2017 and 2018, Hilton was individually voted the number 1 influential particular person in cell with the aid of trade professionals in 2014 and listed as one in every of Europe's digital leaders within the Drum Digerati 2017.

pleasure Bhattacharya, UK and ireland managing director, Accenture Interactive

joy Bhattacharya leads Accenture Interactive within the UK and ireland. Bhattacharya has all the time been interested in innovation and digital transformation, establishing an abilities in each. Bhattacharya has made it his mission to create the most effective customer experiences and enrich the style individuals work and are living. during the last one year Accenture Interactive has been laser concentrated on fixing event-led challenges for valued clientele from Maserati to Radisson. Accenture additionally broke new floor in launching Programmatic functions for shoppers. meanwhile, Bhattacharya oversaw the opening of two new integrated agency areas in Dublin and London.

Liam Brennan, global director of innovation programmes, MediaCom

Liam Brennan is the world director of Innovation Programmes at MediaCom, the place he's assisting develop transformation agendas with a few of MediaCom's biggest purchasers by using statistics, expertise and startups. The Blink group has helped MediaCom customers find new alternatives to convey business and digital transformation – engaged on 40 briefs and initiatives showcasing over 200 technology agencies and startups due to the fact that its inception. outside MediaCom, Brennan is lead mentor for The Wharton college's Entrepreneurship Capstone Programme, assisting students with problem fixing, economic and aggressive analysis, constructing pitch decks and storytelling, and a mentor on the Google Launchpad programme - international acceleration application that helps start-united statesbuild and scale.

Mel Edwards, chief govt officer EMEA, Wunderman​

Mel Edwards turned into appointed global chief govt of Wunderman in September 2018. A catalyst for company transformation, Edwards is diagnosed globally as a frontrunner with a proven record of helping marketers expect and navigate alternate. Edwards has been identified as one of the most influential people in digital advertising and marketing and promoting on many occasions. ahead of Wunderman, Edwards served as chief of M&C Saatchi's Lida.

Natalie Cummins, chief government officer, Zenith UK

In July 2018, Natalie Cummins changed into promoted to chief government of Zenith UK after three years as its managing director. She performed this on a 4-day working week and as a lone mother or father of three little ones. during the last yr, Cummins – alongside the Zenith management group – has persevered a two-year run of one hundred% customer retention, keeping surprising customer relationships in the right quartile of the advertising business. This past yr has also viewed a boom in customer soak up of Zenith’s enjoyable statistics items, including company Contribution, which is a private focal point for Cummins.

Rob Pierre, chief govt officer, Jellyfish

in view that launching Jellyfish in 2005, Rob Pierre has grown the company to over 500 people working throughout Europe, the us, South Africa and Asia Pacific. within the remaining one year on my own, Jellyfish has opened 4 new workplaces, together with one in new york, taking the total number to 11. company accolades in the ultimate three hundred and sixty five days encompass agency of the yr for Digital advertising at the Drum community Awards and at the DADI's, a Drum Search Award for Experian and a good 30 rating in the Sunday times overseas tune 200. Pierre changed into also acknowledged as a regional finalist within the EY Entrepreneur of the year 'Scale Up' category.

Karen Boswell, head of innovation, Adam & Eve/DDB

Karen Boswell leads initiatives throughout all of Adam & Eve/DDB's inventive disciplines items and features, and all clients and agency partners. Having instigated a tradition of high quality disruption, Boswell help groups and consumers alike study issues differently; always difficult the norm, lifting the bar and developing new guidelines. Over the remaining yr, Boswell has incubated three consultancies that now operate as up-circulate strategic features, including data and insight 2.0, brand journey and company Acceleration. Boswell additionally centered a tech startup in her spare time - ardour project THEI.A, a bespoke neural community that powers real-time personalisation within digital fact.

Debbie Vavangas, UK lead, IBM iX

Debbie Vavangas is an govt partner at IBM, where she leads digital strategy and iX for UK and ireland, alongside being an executive companion for the Digital@BP and VWG bills. iX is domestic to over seven-hundred creatives and due to the fact that moving into the function six months in the past the practice has grown considerably in signings and has remarkable growth in team morale, size and earnings. Over the final year Vavangas has created a community of innovation hubs for BP that center of attention on growing experiences that exceed all expectations of the client and its valued clientele. Vavangas has elevated this fashion of working with Audi VW community. She's a proud sponsor and pioneer of 'LGBTQ' and 'women in technology' IBM societies and is a intellectual health first aider.

Matt sweet, world lead, IBM IX

Matt sweet is the global chief for IBM iX, a global professional capabilities business enterprise that helps purchasers reinvent their enterprise with the aid of design. candy leads a global crew of over 16,000 creators and makers across a studio network of 42 studios, who blend approach, technology and creativity to address every client problem. he is a familiar public speaker and blogger on the influence of design riding business reinvention, consumer experience and digital transformation. In 2017, he became elected onto the significant Council of BIMA, to soak up the function as the chair of the BIMA expertise neighborhood and Council.

Nigel Vaz, chief government officer EMEA and Apac, Publicis.Sapient

Nigel Vaz serves as Publicis Groupe's world lead of digital company transformation and leads the Publicis.Sapient company across the EMEA and APAC areas. He held quite a lot of leadership positions with Sapient earlier than its acquisition by using Publicis Groupe and helped to build Sapient into one of the vital largest digital expert capabilities groups within the UK from a startup within the space of a decade. He went on to steer the Sapient company in EMEA and APAC and its evolution to SapientNitro, in addition to playing a key function in the a success integration of Razorfish to create SapientRazorfish in the Publicis.Sapient digital enterprise transformation hub. In his latest position, Vaz acts as strategic guide on complex transformation initiatives for customers including Lloyds Banking neighborhood, BNP Paribas, Carrefour, M&S and Unilever.

Nick Baughan, chief executive officer, Essence

Nick Baughan, chief government officer of Essence, has been pivotal in helping his enterprise to define the up to date company model, encouraging manufacturers take handle of their media whereas concurrently improving the company's talents across the digital spectrum and beyond. during the last twelve months, Baughan has concentrated on strengthening his group, enabling Essence to bring superior-in-category analytics, strategy and activation across all media and practice it to the realm's main brands. beneath Baughan's management, Essence has grown 25% while having fun with a one hundred% retention expense for existing clients. Baughan has overseen groups that delivered world class work for Google throughout Pixel and residential, welcomed BT and delivered floor-breaking work for marketers who like to lean in.

David Levin, creative director, That Lot

David Levin has had a busy year. In July his social agency That Lot became acquired by Weber Shandwick, permitting the company to supercharge its providing and ramp up boom. Levin has long gone from intern to news writer, freelancer to drummer and from the creator/producer of facebook leisure channel to fitting a bespoke social media guru for manufacturers, broadcasters and celebrities. a few of That Lot’s biggest customer successes have come this yr, as smartly. Channel four and E4 have taken pole place as the most considered UK broadcasters on facebook, while the agency helped Jamie Oliver launch a junk meals campaign on Instagram which made information all over the world. That Lot also produced the realm’s first Snapchat spin-off drama. Levin’s acquired big plans for the long run, from social-first, resourceful masterplans at That Lot and techniques to inspire trade round racial discrimination in the trade itself.

Lindsay Pattison, chief customer officer, WPP

Lindsay Pattison become closing week promoted to chief client officer at WPP after a yr serving because the first-ever global chief transformation officer for WPP and its GroupM community. In both these roles, Pattison led the method on how to adapt company fashions and capabilities to stronger serve consumers, and headed programmes focusing on ability and management. previously Pattison changed into chief executive officer of Maxus world, with accountability for 3,000 staff across 55 markets. Pattison is a passionate suggest for enterprise leaders taking significant motion to increase gender equality. In 2016 she launched 'stroll the talk', an initiative to help senior Maxus women to beat the practical, cultural and psychological obstacles to reaching their advantage. WPP has now adopted this globally and via the conclusion of 2018 just about 1,500 ladies can have ‘Walked the talk’.

Nick Farnhill, chief govt officer, PublicisLondon/Poke

Nick Farnhill is a founding companion and chief executive of Poke and chief govt of Publicis London. His focus is on starting to be digital communications and experiences for Publicis UK valued clientele that include EE, Huawei, Google, Ted Baker, Heineken, Morrisons, NBC and Garnier. In 2010, Farnhill launched The Lovie Awards to rejoice the brilliant and provoking things linked through the internet's many tentacles. He continues to co-chair the Awards. Farnhill is also an advisory board member of independent film streaming carrier Mubi and non-government director for countrywide Citizen carrier. Partnering with Hackney Council and Hackney community school, Farnhill co-headquartered and launched the Tech city Apprenticeship in 2013. The initiative became developed to principally help young people meet the potential and employment wants of the becoming expertise cluster across the Shoreditch and historical highway area.

Steve King, chief government officer, Publicis Media

As chief executive officer of Publicis Media, Steve King oversees the media hub of Publicis Groupe, some of the biggest communications networks on the planet. he is accountable for its global company brands, Starcom, Zenith, Digitas, Spark Foundry, Blue 449, Performics, and Publicis Media Precision, which manages programmatic for more than a hundred twenty five shoppers globally. earlier this year he launched Publicis Media's Commerce practice committed to aggregating and scaling Publicis Media's commerce talents globally to span method and acceleration, media and funding, and content material and merchandising, working alongside Publicis.Sapient and Publicis Communications to bring together expertise, infrastructure, media and artistic for an conclusion-to-conclusion commerce providing. moreover, King performed a leading role within the creation of Publicis spine, which fuses collectively Publicis Groupe's facts belongings, expertise and skill to power and hyperlink advertising and digital enterprise transformation.

Mark read, chief executive officer, WPP

Mark study took on the most excessive-profile vacancy in company land in September when he changed into named Sir Martin Sorrell’s successor as WPP chief govt. examine brings to the publish big digital pedigree having served for 12 years as head of method after which chief executive of WPP Digital, and over three years as global chief executive of digital company network Wunderman, WPP’s biggest enterprise. A two-time winner of The Drum’s Digital individual of the yr award, examine’s first main act as WPP chief government was to fold creative agency Y&R into digital store VML, perhaps a sign of things to return throughout his reign at the correct of the world’s largest marcomms company.

David Burgess, director, Deloitte Digital

David Burgess started his profession as a design consultant at reading Room, progressing during the enterprise to turn into UK chief govt of the enterprise with a group of a hundred and ten and a turnover of £9.6m. Burgess sat on the analyzing Room neighborhood board, which oversaw the foreign growth of the business and the sale of its UK operations to Idox for £5.6m. Burgess is now a director at Deloitte Digital the place he leads groups specializing in large scale digital transformation initiatives within the public sector. he's focused on projects which deliver value via technical delivery, design thinking and organisational transformation.

man Wieynk, chief executive officer Western Europe, Publicis

As a member of the Publicis Groupe UK board, man Wieynk has led the transformation of Publicis international UK's 'micro community', along with Publicis London, Poke, Arc, August and Baker road Productions. As part of his European remit, Wieynk has been focused on helping a much wider transformation inside Publicis Groupe, forging a collaborative approach between Publicis Communications, Publicis Media and Publicis Sapient referred to as Publicis interior. He also leads the Heineken business globally. ahead of joining Publicis, Wieynk spent 17 years at AKQA.

Michael Olaye, chief govt officer, Dare

Michael Olaye is the executive executive officer of Dare, a digital creative company with hub offices in London, Bristol and Stockholm. Dare is part of marcomms company inner concepts group. Olaye leads inner concepts neighborhood's complete tech imaginative and prescient, accountable for its technical collaboration, trade idea management and superior expertise incubations. he's a daily guest speaker and decide, an guide to tech startups. Olaye has additionally been honoured within the BIMA one hundred and is one of Creativepool's suitable one hundred influencers. Olaye assists on the faculty of Arts & Communications 2.0, working with up-and-coming trade ability and helps local communities in the London boroughs through the Future First Alumni programme, each as a supporter and visitor speaker.

if you're drawn to studying more concerning the Drum's Digerati, contact Toyin Rodwell by way of toyin.rodwell@thedrum.com.


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Predictive Analytics in 2018: What’s Possible, Who’s Doing It, and How | killexams.com real questions and Pass4sure dumps

In 2009, Netflix offered $1 million to anyone who could improve the quality of its recommendation engine by 10%. It took two years, but a team finally won. Netflix paid the bounty—then ignored the code.

As it turned out, the enhanced algorithms “did not seem to justify the engineering effort needed to bring them into a production environment.”

Not only did the winning prediction engine fail to scale economically, it also addressed an outdated problem: The shift from mail to streaming during that same two-year window gave Netflix all the data it needed to develop newer, better algorithms.

Predictive analytics, in other words, wasn’t a panacea. Nor, in the decade since, has it become one. But, in 2018, incremental gains no longer cost $1 million either:

  • You have more data;
  • Storage is cheap; and
  • Cloud computing is almost infinitely scalable.
  • This post details those changes and shows how several businesses—and not just behemoths—have cultivated the predictive analytics landscape.

    What’s changed in the last decade? 1. More data, more storage, more computing power

    Massive, cloud-based repositories of customer interactions, often called data lakes, are the raw source material for predictive analytics applications.

    Many companies have taken advantage of cheap cloud storage to stow away data for years—without even considering its potential use. (How many neglected data points do you have in Google Analytics, Google Ads, MailChimp, Marchex, Stripe, and similar services?)

    That dual growth in scale—of data collected and accessibility to it—has solved two primary challenges of predictive analytics implementation.

    Historically, raw computing power has been the other. As Andrew Pearson of Intelligencia notes, “Without significant hardware investments, predictive analytics programs either weren’t possible or too slow to be useful.”

    That, Pearson continued, has also changed: “Cloud-based analytics systems have added massive computer power into the mix.” Increasingly powerful systems cracked open the door for real-time predictive analytics.

    2. A world of real-time predictions

    For some, the age of “real-time” predictive analytics is here. Judah Phillips, the co-founder and CTO of Vizadata and founder of SmartCurrent, explained:

    We already live in a world of “real-time” predictive analytics. A simple predictive analysis is your arrival time in Waze. A more complex real-time prediction occurs billions of times worldwide every millisecond in matching certain types of digital advertising.

    Further, companies like Mintigo and Versium now offer real-time solutions for lead scoring, showing that the transition is technically possible. Possible, however, doesn’t mean perfect. Sam Underwood, a vice president at Futurety, acknowledged the complexity of necessary integrations:

    Especially in the mid-market world, the tools that gather data to turn into predictive modeling—CRM systems, social media aggregators, logistics, and purchasing systems—often do not have friendly APIs or other easy mechanisms with which to quickly gather and interpret data.

    That disconnect still thwarts even the most fundamental business cases for real-time predictive analytics. David Longstreet, the chief data scientist at FanThreeSixty, offered an example:

    In our world of sports and entertainment, for example, most sports teams do not know how many people are in a stadium for a game. Teams know how many tickets were distributed; however, they do not know in “real time” how many people are in the venue or stadium during the event.

    That knowledge gap hampers efforts to staff and stock the stadium appropriately. It’s also why interest in predictive analytics is almost universal, even if it vastly outpaces adoption.

    3. Slow adoption but soaring interest

    So how many businesses are actively using predictive analytics? According to research from Dresner Advisory Services, about 23%, a figure essentially unchanged from the prior year.

    predictive analytics adoption

    Less than a quarter of businesses are using predictive analytics—though almost all aspire to do so. (Image source)

    Interest, however, exceeds implementation. The same research suggests that 90% of businesses “attach, at minimum, some importance to advanced and predictive analytics.”

    So which questions are those 23% answering with predictive analytics? Let’s take a look.

    Which questions can marketers answer with predictive analytics?

    “They want to predict everything,” according to Underwood. And who wouldn’t want to know the exact foot (or web) traffic by month, day, and hour to streamline staffing (or allocate server resources)?

    But, Underwood continued, he tries to focus clients on “the one thing that, if we could predict it for you, would revolutionize your business.”

    In digital marketing, Phillips outlined myriad use cases for predictive analytics, including the capability to predict:

  • which advertising will be most effective—however you define effective.
  • which marketing campaigns, channels, touches, behaviors, and demographics are contributing to a business outcome, a form of “machine learning–based attribution.”
  • which segment, test, or personalization a user is most likely to respond to.
  • the probability of users to click on an ad, to download a whitepaper, to respond to an email, to respond to an offer, and other customer response you define.
  • which leads will convert—however you define conversion.
  • which customers will buy one or more products for a cross-sell or upsell.
  • the number of purchases or revenue that will occur in the future.
  • which customers will have high/medium/low lifetime value.
  • customer churn.
  • The novel opportunity of predictive analytics, then, is not what you can predict but the fact that you can predict. The historical data you currently analyze can probably become a prediction.

    Just make sure you have the data.

    What do you need to get started with predictive analytics?

    Data, data, and data. “Priority 1A and 1B are data sources,” stated Underwood. That’s true whether you plan to license software or hire an outside organization. (Both options are detailed later.)

    All uses require training data. That training data, in turn, is used to build a predictive model to apply to current data. “The only limitation we’ve run into,” Phillips noted, “is a company’s available data for training.”

    How much data is enough? According to Phillips:

    A few thousand records with a sufficient amount of positive and negative outcomes can be sufficient for marketing, sales, and product prediction.

    Not all data is created (or stored) equally

    “You have to understand—I grew up tearing tickets.”

    FanThreeSixty’s Longstreet has heard that same explanation from venue managers who have spent countless hours counting stacks of stubs after games. It’s a reason why vital data sources may not be easily accessible, or accessible at all.

    In stadiums, Longstreet explained, point-of-sale machines and ticket scanners exist for a single purpose—to complete transactions quickly and keep lines moving. Those systems do not store data efficiently for extraction, nor can they handle incessant server requests (unless hungry fans don’t mind waiting).

    For Underwood, clients tend to fall into one of two buckets, with half in each:

  • “The ideal client has an internal database set up and ready to go. We pull in the data, build the model, and are off and running.”
  • The other half have a mix of data sources, which inevitably include an offshore SQL database (or ten) managed by an external vendor whom no one can track down.
  • Stitching data sources together is a major development project that may require creating custom connectors, setting up third-party FTP drops, and other complex but thankless tasks. That work, however, is necessary: Models and their predictions are only as accurate as the data they’re built upon.

    Don’t forget external data sources

    Not all data comes from internal sources, either. External data sources, like weather reports, are often a critical addition to data lakes, especially for small businesses. As Underwood explained:

    Restaurants may use analytics to trigger email sends; for example, we can set up the email platform to sync with National Weather Service data to send an email about iced tea when the temperature in a given metro area is above 90 degrees.

    Likewise, we can trigger an email to send to customers in a given city if the system detects wind gusts of 40+ MPH. Both of these use cases reach consumers in a key moment of need, negating downstream ad spend and beating competitors to the punch.

    So you have a large, well-organized dataset. What do you do with it?

    How do you turn data into predictions?

    While the limitation of insufficient data has faded, another remains:

    Companies require either a dedicated team of data scientists to parse through these sets, or a software suite powerful enough to do so rapidly. For most small and medium-sized businesses, this usually means settling for subpar software, or forgoing it entirely.

    For businesses of all sizes, solutions branch into two options:

  • Purchase software and create predictions in-house.
  • Pay an outside vendor to develop models and visualizations for you.
  • 1. Predictive analytics software

    The marketplace for predictive analytics software has ballooned: G2Crowd records 92 results in the category. Pricing varies substantially based on the number of users and, in some cases, amount of data, but generally starts around $1,000 per year, though it can easily scale into six figures.

    G2Crowd lists both IBM’s SPSS Statistics and SAS’s Advanced Analytics as market leaders at the enterprise level. Along with RStudio, the pair are also tagged as leaders for mid-market companies; only IBM retains a place in the “Leaders” quadrant for small businesses.

    Historically, however, even industry-leading predictive analytics software hasn’t been a simple, jump-right-in experience. Take these two examples from IBM’s SPSS Statistics and RapidMiner:

    ibm spss statistics screenshot

    rapid miner screenshot

    While these platforms are powerful, users must format data files, link nodes, and develop visualizations. Learning how to do this—and having the time to do it—is a specialized, full-time job. (To believe otherwise is to expect a Microsoft Word license to write your Great American Novel.)

    Not surprisingly, the market is shifting. RapidMiner has rolled out a SaaS beta that, with a bit of manual adjustment, translates an Excel sheet full of, say, employment data to a prediction of employee retention:

    rapid miner saas excel sheet

    A dataset in Excel—a starting point in which most marketers are already comfortable. rapid miner intake

    RapidMiner parses the Excel file prior to crunching the numbers. rapidminer predictive visualization

    The resulting visualization shows the tool’s prediction performance and correlations between datasets and retention.

    Some companies, like Vizadata’s Phillips, see the user-friendly SaaS model as the future:

    We are democratizing data science, so that people with limited or no data science or engineering skills can predict. You simply upload your data and click next. We do all the heavy lifting.

    Our intelligence determines your dependent and independent variables and the type of analysis to run. You can go with our selections or override them—from regression, where we can do forecasting and optimization, to both binary and multiclass classification, where we can predict the probability of outcomes.

    vizadata screenshot

    User-friendly SaaS models make predictive analytics more accessible to marketing teams without data scientists.

    Like Vizadata, MIT’s Endor pursues this path. The platform uses a query-builder to allow anyone to ask questions like “Where should we open our next store?” or “Who is likely to try product X?” It then mines targeted datasets to provide answers, often in a matter of minutes.

    The inclusion of tangential datasets that fall outside consideration—or feasibility—for human observers is a recurring advantage of predictive analytics. Endor’s creators offer an example:

    A marketing department for a bank asks, “Who is going to get a mortgage in the next six months?” Machine-learning engines may detect a pool of, say, 5,000 customers who have a bank credit card and a high credit score, and are married—many of which may be false positives.

    Endor detects more specific clusters of, say, couples about to get married or going through a divorce, founders who recently sold their startups to Facebook, or customers who recently graduated from a local real-estate course.

    Of course, if you want to outsource the process entirely, outside vendors can organize your data, build models, and visualize predictions for you.

    2. Outside vendors Agencies offering bespoke solutions

    For most clients, Futurety starts by identifying the key business question—not a specific metric or visualization. Clients may come in for one-off projects, annual re-runs of their data, or ongoing work.

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    Webcast, October 17th: How to Solve Your Marketing Data Nightmare

    “The end result is not always clear at the beginning,” Underwood explained. “When we’re delivering to someone close to the outcome, like a marketing manager, they’re typically happy with the model, the finding, and the math behind it.”

    The “end result” could be several things:

  • Integration with a third-party platform, like an email client, to automate predictive messaging.
  • Plain-text predictive answers to guide practitioners.
  • Robust visualizations to demonstrate the process and value to the C-Suite.
  • At the end of each engagement, Futurety delivers the model back to the client for management and maintenance.

    Predictive analytics at work
  • Futurety has a small business client that helps aspiring performing arts majors gain admission to their dream college. But few high schoolers have broad knowledge of good programs. More often than not, they know only one name: Julliard.
  • Futurety trained its model on three years of placement data. Then, using new student data entered into a common portal, predicted where students would get accepted and succeed academically.
  • The predictive analytics model, which Futurety updates annually, delivers a simple list of recommended schools for students based on factors like grades and exposure to different musical or artistic styles.
  • The model takes into account whether past placements graduated or won awards.
  • All-in-one niche providers

    FanThreeSixty serves a narrow market: sporting venues. Because they work with a comparatively consistent dataset—season ticket, concession, and souvenir sales—they know the range of business questions, data outcomes, and relevant visualizations.

    This consistency incentivizes niche vendors like FanThreeSixty to develop proprietary dashboards to roll out to all clients.

    The interface allows Longstreet’s team to keep data science in the background: “The secret of machine learning is when you’re being prompted behind the scenes.”

    Distilled fully, FanThreeSixty’s goal (and Longstreet’s explanation of his role at dinner parties) is to “help teams sell more tickets and hot dogs.”

    Predictive analytics at work
  • FanThreeSixty mines historical data to see which concessions are most commonly purchased with a hot dog at a Major League Soccer venue.
  • If a customer purchases a hot dog, concession staff are prompted to ask whether a customer would like to add the most popular accompaniment. That recommendation—a prediction of fan desire—changes based on other variables.
  • Predictions consider more than 20 datasets—everything from the home location of season ticket holders to the weather—to tailor messaging before, during, and after matches.
  • During cold-weather games, for example, FanThreeSixty can automate push notifications with tailored coupons, like buy-three-get-one-free hot chocolate for a family of four.
  • Whether solutions are internally or externally managed, they‘ve long been common in enterprise businesses.

    Predictive analytics use cases at the enterprise level

    Marketing departments in large organizations have used predictive analytics for years:

  • AutoTrader. AutoTrader uses data from its 40 million monthly visitors to better understand the sometimes lengthy customer journey. They built propensity models based on search behavior and created high-value lookalike audiences.
  • Editialis. The French publisher uses predictive analytics in its email campaigns to “anticipate engagement at an individual level.” As a result, they’ve seen click-through-rates increase “dramatically.”
  • Predictive analytics can also coordinate offline and online interactions, with two clear use cases for marketers whose companies have physical products or storefronts:

  • Improved pricing. Smartphone data registers in-store browsing habits to improve online or offline marketing targeting, approximating the advantages enjoyed by ecommerce companies.
  • Inventory management. Full warehouses cost money; empty shelves cost money. Folding online data, such as search patterns, into sales data can better manage inventory, especially at a regional and local level.
  • In addition to external marketing campaigns, predictive analytics also supports internal project management. Large marketing campaigns have many moving parts—a new ad campaign needs new creative, new copywriting, new landing pages, etc.

    Coordinating the involvement of those teams and accurately estimating the time-to-launch is complex. Many fail to get it right, sometimes at great expense.

    whiteboard planning

    Marketers and software businesses may use predictive analytics for internal project management in addition to external campaigns.

    Predictive algorithms, as McKinsey notes, use a wider lens that captures historical patterns and unique project elements in a single frame:

    While every development project is unique, the underlying complexity drivers across projects are similar and can be quantified. If companies understand the complexity involved in a new project, they can estimate the effort and resources required to complete it.

    Predictive analytics models “take into account not only the complexity of the project (both the functional and implementation aspects) but also the complexity of the team environment.”

    Predictive analytics at work:

    More accurate internal project management, in an example McKinsey offers, can have a major impact:

  • A company initially planned a product update to take roughly 300 person-weeks of effort, an estimate based on the limited number of changes between the current product and a new design.
  • However, that estimate failed to take into account the fact that planned updates would affect many different teams. Predictive analytics models did take it into account and estimated that the project would take three to four times as long.
  • As a result, the company limited the work to the original product team, enabling them to deliver the update on time.
  • In addition to helping companies solve internal and external challenges, predictive analytics is also the foundation for some businesses.

    Building a business on predictive analytics

    Ken Lazarus, CEO of the recruiting platform Scout Exchange, has an advantage—the company has been around for only five years.

    That means that the company’s data sources are already primed for extraction into its predictive models that pair companies with the right recruiter.

    scout exchange processScout Exchange’s predictions pair companies with the right recruiter.

    The single best predictor of job placement, Lazarus and his team have found, is the track record of job recruiters. In contrast, pairing the right job description with the right resume remains exceedingly difficult.

    “Job specs are horrible,” he lamented. “The data isn’t on the paper. CVs are pretty horrible, too.” (Data augmentation, such as skills testing and video interview decoding, Lazarus noted, offer potential improvements.)

    Nonetheless, holes remain. Candidates will never disclose negatives on their resume, and important information might forever remain “non-data,” such as whether a candidate is a good “culture fit.”

    Scaling data gathering

    Scout Exchange has honed its predictions by focusing on enterprise customers—its algorithms feast on hundreds or thousands of openings from Fortune 500 clients.

    As a result, the platform takes in roughly 1 million data points monthly, with each new job posting yielding an additional 50 data points.

    scout exchange platform

    Higher employer ratings indicate an employer is more responsive than his or her peers. Likewise, higher recruiter ratings suggest a recruiter is more likely to succeed in submitting acceptable candidates than his or her peers.

    Still, human assessment by a recruiter—and their client—is necessary. Lazarus drew a parallel: “Would you let machine learning pick your wife? No. But would you let it pick the right matchmaker to help you find a spouse? Yes.”

    Those who are trying to solve the most complex human issues aren’t even in the business world.

    Predictive analytics with life or death consequences

    The greatest challenges for predictive analytics are those that deal with complex, individualized human behavior, such as the likelihood that a patient or crisis-line texter will commit suicide.

    Because success or failure is measured in human lives, these challenges are also the most urgent. And while these projects operate beyond the scope of marketing and business, they suggest the potential for predictive analytics as it evolves.

    “REACH VET is not about trying to find the veteran who’s sitting in the car in a parking lot with a gun in his lap,” Aaron Eagan, Veteran Affairs deputy director for innovation told a Washington conference.

    “What we found,” Eagan continued, “is that veterans at highest risk of suicide [also have] significantly increased rates of all-cause mortality, accident morality, overdoses, violence, [and] opioids.” Proactive alerts that trigger physician check-ins have improved primary-care appointment attendance and reduced hospital admissions for mental health issues.

    crisis text line

    The project is similar to a collaboration between Periscope Data and Crisis Text Line, a text-based suicide hotline.

    Leaning on natural language processing and predictive analytics, the program analyzed conversations, forecasted trends, and trained more than 13,000 volunteers. The results?

  • Wait times decreased to less than 5 minutes, an operational goal.
  • Capacity increased by 10% during peak periods.
  • Responses were prioritized based on machine-identified urgency.
  • Endor’s technology has taken on similarly serious challenges. Using 15 million data points from 50 known ISIS supporters, Endor identified 80 lookalike accounts in less than half an hour, with only 35 false positives—expert investigation was still necessary yet feasible.

    In a collaborative project with the U.S. Defense Advanced Research Project Agency, the platform also analyzed mobile data to identify patterns to predict future riots.

    Conclusion

    Predictive analytics is not immune to criticism: GDPR rebuffs some of the same collection methods that swell data lakes. And not all predictions, even the most accurate, are well-received. (Famously, Target unwittingly informed a father of his teenage daughter’s pregnancy based on seemingly benign shopping habits.)

    Predictive analytics experts point out that their algorithms search for patterns among values, not the values themselves. Regardless, insufficient data is unlikely to hold back the expansion of the industry—the IoT, wearables, and other data collectors already supplement traditional web and app analytics.

    User-friendly SaaS platforms are still an emerging opportunity. For most businesses, creating models and predictions from historical data still requires a dedicated employee to navigate complex software solutions or the outsourcing of that work to a vendor.

    For those postponing predictive analytics projects until the SaaS options are more mature, you would be wise to keep filling your data lake.


    Pro rugby club enlists IBM to predict when players will be injured | killexams.com real questions and Pass4sure dumps

    Leicester Tigers in action against Worcester WarriorsLeicester Tigers in action against Worcester Warriors Sam Dredge reader comments Share this story
  • One of the world’s leading rugby teams is about to learn whether the sport, once described as “a ruffian’s game played by gentlemen,” can benefit from the genteel field of science.

    The Leicester Tigers are the most successful English rugby union club of the past 25 years, winning the Premiership title a record nine times and twice capturing the European championship. Later this month, they’ll play in their eighth consecutive league final. In an effort to maintain that impressive success, the club is working with IBM to use statistical analysis software in assessing the likelihood of injury.

    In the past, Big Blue has used its SPSS Modeler predictive analytics software to help clients like Coinstar find the most profitable location for its coin-conversion machines and show the Memphis Police Department where to deploy officers to reduce crime. It believes the same analytical approach can help the Tigers optimize training and keep the best players on the field.

    Although the company’s system can gather thousands of variables, only a surprisingly small number really matter, said Erick Brethenoux, IBM’s director of Business Analytics and Decision Management Strategy.

    “We’ve found that on average, maybe 15 to 20 variables are more than enough—not a thousand—to be predictive,” Brethenoux said. “When one of those factors gets out of line, we can reduce training in some instances, or prescribe other types of training for a period of time.”

    Players wear equipment during training that captures statistics like heart rate as well as the forces absorbed by rugby’s frequent jarring hits. Data are uploaded to the team’s database, where IBM’s modeling software looks for patterns. Additional info is drawn from player questionnaires that could provide insight into their stress levels and injury history. Leicester used the program for a trial period this season, and the team’s sports scientist, Andy Shelton, said the goal is to monitor the entire squad an entire campaign, gathering minute-by-minute data.

    “We’re at the very early stages,” Shelton said. “We’ve run some models so far on stats that we’ve collected over the past five years and although they need refining, it’s looking very promising in terms of injury prediction.”

    As usual, the devil is in the details. Or, in this case, the data. The success of the program depends not on the analysis, but on the reliability of the data being gathered, said Will Carroll, who writes the Under the Knife column about sports injuries for SI.com.

    “How do you measure fatigue if you can’t directly measure it?,” Carroll said. “Data analysis is only as good as the data.”

    As professional rugby has grown in popularity around the globe in recent years, the influence of money has grown as well. With that maturation comes economic constraints for some teams, even successful ones like the Tigers. Although they dominated the British leagues during the past decade, Leicester has met strong challenges from some of Europe’s top clubs. One reason for that is English teams have a salary cap of 4.5 million British pounds (about $7.2 million), while the top French clubs top out at about 7.2 million pounds ($11.5 million). If that sounds like a situation ripe for the Moneyball approach popularized by baseball’s Oakland A’s, you’d be right. Shelton said teams with big payrolls can easily sub in a top international player when one of their own stars goes down, but Leicester doesn’t have that luxury.

    “In one game, it might not make a difference, but over the course of a season and in the big games toward the end of the season, that’s when it makes a big difference,” Shelton said.

    In addition to keeping their best players healthy, Shelton said IBM’s system could also be used to develop young players from their sports academy into long-term productive pros. “All of this is just a tool to aid the coaches and help the players along,” Shelton said. “None of this will ever replace coaching or talent. If we can keep our front-line players fit for longer and if we can give a little bit of help to the coaches to select academy players or pick up on ones they may not have noticed, then it can only be beneficial.”


    Xerox Channel Chief Peterson On The 'Huge' Push For SMBs, Apps And New Partners | killexams.com real questions and Pass4sure dumps

    The high-stakes drama at Xerox earlier this year hasn't slowed down the company's efforts at boosting innovation and expanding into new business segments with a broader set of reseller partners.

    That was one takeaway from our visit this week with Xerox executives in New York, including Pete Peterson, president of Xerox Channels.

    [Related: Xerox Launches New Printer Apps For Salesforce, QuickBooks, Concur]

    The company said Wednesday that its line of ConnectKey-enabled devices will now include access to key business apps such as Salesforce, QuickBooks Online and Concur. In addition, partners can now sell and resell apps from the newly "e-commerce-enabled" Xerox App Gallery.

    This week, Peterson sat down with CRN to talk about those moves as well as Xerox’s success so far at moving into small and midsize businesses with the help of a portfolio of A4 devices and an increasing number of solution provider partners.

    “This isn't the old Xerox,” Peterson said. “We're a nimble company, and we're a high-tech company in a really hot space right now.”

    What follows is an edited portion of the conversation with Peterson.

    Should partners be leading with apps? How seriously should partners be looking into apps if they aren't already?

    We're excited, from a channel perspective. This is exciting times to be at Xerox, with the major focus on apps. I do believe it's a differentiator in the marketplace. For sales professionals, any time you can differentiate your offering from a product perspective or a solutions perspective, it gives you a leg up. So I think our partners have embraced it. One early adopter [Just-Tech president Josh Justice] has literally built his business around apps. Not only to differentiate in the marketplace that he sells into, but it's also a revenue and profit stream for Josh and his company. His business model has changed significantly in the last 18 to 24 months, and it's really been because of apps.

    We've had about 400 partners that have gone through this whole training, whether they decide to build their own apps, or acquire, or sell. So we're excited. When you look at other manufacturers in our space, I don't see these offerings.

    How do apps fit with your efforts to recruit more partners?

    In the last 18 to 24 months, we've had a major focus on attracting what we call ‘multi-branded partners.’ Xerox has a fairly unique partner ecosystem. We have our agents, which are mono-branded—we have a contractual agreement where they only sell Xerox. That model was built probably 25 to 30 years ago. And that's been very successful for us. But for us to get at a bigger piece of the market-share opportunity, it's with those multi-branded partners.

    They come in two flavors. The first one is DTPs, or document technology partners. In the U.S. there are probably 2,100 to 2,200 of them. They're very print-centric, and in most cases not a lot of them are leading with Xerox. So we have signed up just shy of 10 percent of them—so just under 200—in the last 18 to 24 months. That business is growing for us. If they've got another manufacturer on their line card, and our products and solutions are a little bit more robust, it makes a difference.

    Then the second route to market in that multi-brand space is the IT resellers. There are roughly 60,000 or 70,000 IT VARs in the U.S., and over 10,000 of them buy something that we sell. And we're only selling to maybe 20 percent [of the 10,000] today. That's a huge opportunity for us to expand our products and solutions into the marketplace. And again, apps is a great way to do that.

    Are apps on multifunction devices starting to move beyond the early adopter phase?

    Yes. I believe there are somewhere in the neighborhood of 70 apps that are now available. About 20 are geared toward the end user, and 50 are geared toward the partner. That's a significant difference from when I joined 18 months ago. We had maybe 20 apps. So we've grown by about 50. The second is, with our new App Gallery, that thing is unbelievable. It's taking the complexity out of the process of buying and even selling apps. … The recent launch of that App Gallery is going to have a huge impact on the growth of this business.

    So you are seeing more partners making a significant business out of apps?

    Absolutely. And I think part of it is, we couldn't see some of it before. If Josh [Justice] sold his app to someone else, that was a transaction that took place outside of our purview. We just didn't have visibility into it. Whereas now we have this central repository—that makes it easier for them, it gives them reach that they couldn't get to on their own. Now they have a platform to do commerce on, which should give them a much bigger aperture to sell their products and solutions. And then obviously it gives us a lot bigger, broad visibility into that activity as well.

    How has adding A4 helped with your push into SMB?

    It's been huge. When we launched our new ConnectKey products in March of 2017, the expansion into A4 gave us a huge footprint. We've had great success so far. It's like any new product—the first three to six months you're working out some of the supply chain [issues] and the market opportunities. But we've seen pretty significant growth. We track it pretty consistently, through a bunch of services, whether IDC or NPD. And we think our devices are making a difference as we've seen our market penetration expand pretty significantly. I think it's the product expansion, and the solutions expansion through our apps.

    Xerox historically has always been viewed as a high-end, enterprise-type solution. And when you start throwing around the words ‘high-end’ and ‘enterprise,’ the first thing that comes to mind is complexity. We're on a maniacal [mission] to make sure we're driving simplification across our business. Whether that's our delivery, whether that's our supply chain, however we interact with our customers and clients—how can we drive a simpler approach to that? This isn't the old Xerox. We're a nimble company, and we're a high-tech company in a really hot space right now.

    Do you think your competitors are vulnerable because they don't have these same app capabilities?

    I can't speak for them, but I'm glad I'm on this side of the line. Because it is a differentiator. For example, the education app [allows] schools to become smarter and more integrated. Better productivity. I was also impressed with the app where you're able to scan a document and turn it into an MP3. Those are game- changers, in my opinion.

    What are you doing to help bring more managed print services into SMB?

    If you look inside of Xerox, our SMB MPS offering is the fastest-growing piece of our MPS business. The early adopters [for MPS] were the enterprise, which makes sense. But in the last year to 18 months, we've seen a significant adoption rate for SMB. We just recently rolled out our XPPS [Xerox Partner Print Services] offerings. I think we've enabled somewhere close to 100 partners in this fiscal year—we've got them certified and enabled so they can better understand the solutions and offerings. We see that as a great growth engine for us in the future. Xerox has been the forefather of MPS. We are the market leader from an MPS perspective, and we see that now transcending into the SMB as well.

    The best way to reach the SMB community is through our IT VARs. That's who they sell to—80 percent plus of their revenue is coming from SMB. That's attractive to us. Xerox could never get there on our own. In my [IT VAR] business, 75 percent plus of that business is A4. A3 represents 25 percent. We're focused on driving that A4 platform through that IT VAR community.

    How are you minimizing overlap between your mono-branded and multi-branded partners?

    When we're signing up partners, we have a pretty structured process—we call it "heat maps." We have this intelligence tool where we're taking our data, taking market intelligence data, to where literally we have about 400 different regions in the U.S. And we go in and say, we know exactly what our market share is there. If we're in a market where our market share is sub-20 percent, we want to expand. If we're in a market where we have what I would call adequate coverage—25 [percent] or 30 percent—I'm not interested so much in signing on new partners. But if I'm in a market where I'm at 5 [percent] or 10 percent, I want to sign as many as I possibly can. It's very tactical. Even if we have a mono-branded dealer [in a region], but we're sitting at 5 [percent] or 10 percent market share, I want market share. So I'm going to co-invest with [mono-branded partners] to do more for us, but if that's not enough, then of course that's when you start looking at the multi-brand opportunities.

    How have the leadership changes in recent months impacted your channel investments?

    The investment piece hasn't changed and hasn't wavered. That was the piece that was attractive to me when I joined Xerox 18 months ago. And you're right, we've had a lot of changes in the last six months, starting with the new CEO, John Visentin. [He] has a strong channels background—he worked for IBM for probably two-thirds of his career, worked at HP in a channel environment. Mary McHugh, who he brought in next, is our chief delivery officer. Very similar—strong IBM background, also worked at Oracle and HP. Very channel-centric. Then, [President and COO] Steve Bandrowczak, who worked for Lenovo and worked for Avnet. So, channel background. Then most recent is [Chief Commercial Officer] Joanne Collins Smee—IBM again.

    So you look at the common denominator—they understand services, they understand channels and the value of channels. And so for folks like myself, we're saying, ‘This is a great opportunity. You can't really go and expand this business until you fix the foundation.’



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