|Exam Name||:||Designing Database Solutions for Microsoft SQL Server|
|Questions and Answers||:||111 Q & A|
|Updated On||:||August 16, 2018|
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70-465 exam Dumps Source : Designing Database Solutions for Microsoft SQL Server
Test Code : 70-465
Test Name : Designing Database Solutions for Microsoft SQL Server
Vendor Name : Microsoft
Q&A : 111 Real Questions
GitLab has published it's working on a brand new device for the facts science lifecycle. Meltano is an open-source answer designed to fill the gaps between statistics and figuring out business operations.
“Meltano turned into created to assist fill the gaps by increasing the normal statistics store to guide client Success, consumer guide, Product groups, and revenue and advertising and marketing,” the group wrote in a publish. “Meltano goals to be an entire solution for facts groups — the name stands for model, extract, load, radically change, analyze, computer, orchestrate — in different phrases, the facts science lifecycle. while this could sound conventional in case you’re already a fan of GitLab, Meltano is a separate product. rather than wrapping Meltano into GitLab, Meltano should be the complete equipment for data people, whereas GitLab is the finished kit for utility builders.”
The purpose of Meltano is to make analytics obtainable to each person, now not just facts professionals. based on GitLab, while the enterprise has event gathering statistics and providing it in a readable structure to company clients with a view to make predictions based on the records, it takes too many steps and tools to finished this.
“The concept of bringing most fulfilling practices from utility building to statistics analytics is a major draw for the statistics team at GitLab. Ideally, all of our work may be accomplished in open source equipment, and could be version controlled, and we’d be able to tune the state of the analytics pipeline from uncooked information to visualization,” GitLab wrote.
The device presently most effective supports Postgres with plans to add Snowflake within the near future. The enterprise is aware of it will should support a wide selection of database types, and its hunting for contributions from the open-source neighborhood to aid meet that goal.
“As an open supply device, we believe Meltano will make a huge difference for groups with out an awful lot funds to invest in facts analytics. It’s a new field for a lot of agencies, and we need to do every little thing we are able to to make it less demanding for groups and company to entry their records and make enhanced choices,” GitLab wrote.
What if the large design area for information-driven application may be correctly mapped and explored with the intention to have tailor-made, optimized options? Researchers from Harvard mix analytical models, benchmarks, and desktop learning to make this possible.
Stratos Idreos is an Assistant Professor at Harvard, and leads the information programs Laboratory (DASlab). Idreos additionally occurs to be an ancient pal and colleague in research from the mid-zeroes, and or not it's at all times a pleasure to catch up.
Idreos' work in Harvard is featured a little bit atypically for an academic researcher. that's, in a visual, fairly convenient to navigate, and compelling way. there are many issues we could spend hours talking about, however the one that immediately gets attention is self-designing information methods.information constructions
statistics buildings are how we save and entry facts. an information constitution design, as described with the aid of Idreos and his crew in a contemporary publication, consists of 1) the statistics organization, 2) an not obligatory index, and 3) the algorithms that guide fundamental operations (comparable to put, get, replace).
All algorithms cope with statistics and most often the design of an algorithm starts by way of defining an information constitution so that you can allow faster issue fixing by minimizing computation and facts movement.
feasible techniques of designing algorithms and information techniques are restricted via selections in statistics constructions. for example, we are able to most effective make the most of an optimized sorted search algorithm if the records is sorted and if we can hold the facts efficiently in such a state.
This makes statistics structures probably the most fundamental accessories of computing device science, and here is why they're on the core of all subfields, including statistics systems (relational, key-value, graph, etc).
each and every facts constitution design is a compromise between the examine, replace and memory amplification alternate-offs. photo: DASlab / Harvard
information buildings don't seem to be something everyone understands and might without difficulty use. This class of knowledge is regular among database directors (DBAs) for example, due to the fact that they should work with statistics constructions to pleasant tune their techniques.
however to move past that, to synthesize and mix, or invent, information structures, and to be mindful the most desirable design selections when building facts techniques, is whatever that a choose few individuals on earth can grasp.
Idreos, being himself a type of few, is working towards a framework to take probably the most burden off the shoulders of each DBAs and gadget designers.information Calculator: Mapping the design area
knowledgeable information device designers are briefly supply. And even for them, the manner of designing and implementing a knowledge system is advanced and dear. there is an enormous design area of a combination of facts constructions, workloads and hardware configurations to explore. Making the correct choices is advanced, and it takes time.
people should give lots of notion to their design, and then put into effect it and examine it to peer the way it behaves. Idreos' intention is to automate this method as much as feasible. the first step is what he calls a periodic desk of facts structures.
The periodic desk of elements in chemistry geared up points right into a commonplace structure, a design house according to their residences and components. This helped classify and explain connections among current elements, and provided hints about discoveries no longer yet made.
A periodic table for statistics techniques. picture: DASlab / Harvard
here is what Idreos wants to obtain with the periodic desk of facts buildings, or statistics Calculator. The method is to map information structures and their houses in this desk, and then use it to discover the mammoth search house of different mixtures.
information gadget design, explains Idreos, is a function of three elements: facts buildings, workload, and hardware. for example, a certain index can also operate very well for reads in-memory, but not so smartly for writes on-disk.
Idreos and his team have created analytical fashions supplemented via benchmarks and desktop gaining knowledge of that may estimate how smartly-acceptable a design may be for definite workloads and hardware configurations. This has some very unique purposes.Get your RocksDB 1.000 instances off, optimize within the cloud
Would you want to get 50 percent superior performance out of your latest device, or to retain the existing stage of efficiency, however with half the hardware? this is the kind of impact effective gadget tuning can have.
Idreos' work is massively formidable, as it touches upon what is the state of the art today, and guarantees to drastically improve on this. to draw on some concrete examples, consider of techniques reminiscent of Oracle's self-tuning database, or an identical offerings such as the ones from ScyllaDB or MemSQL.
historically, notes Idreos, IBM and Microsoft were among the pioneers in exploring adaptive statistics techniques. historically, the focus has been on tuning indexing. Now here's increasing to other knobs, and this, Idreos speculates, is what Oracle does too.
Idreos' work is distinct in that it does not just tweak current records constructions akin to indexes as an instance, but it can additionally reconfigure them to create new ones dynamically. Or as a minimum, here's the vision.
in the interim, DASlab's first implementation can also work otherwise from the Oracles of the realm, but looks to have the same, albeit magnified, effect. DASlab have worked with RocksDB, which Idreos says they have got managed to reconfigure to achieve efficiency that may be from 1.000 to 10.000 instances improved for a similar workloads.
additionally: huge information architecture: Navigating the complexity TechRepublic
a different promising application may well be tiering for cloud providers. As further and further applications and records circulation to the cloud, the issue of what to retain in fast access media and what to movement to tape turns into more and more essential.
Tiering is the trouble to reply the question of what hardware to use for storing data, or in a selected desktop, wherein memory area to shop facts. Idreos says that facts Calculator can seize such features.
or not it's an optimization issue: for a particular workload, and funds, discover the most reliable equipment, hardware, and memory allocation.
DASlab's research can be utilized to the use of open supply statistics codecs in the cloud for such eventualities. Idreos says they will need not less than 365 days of analysis for this, and the tough part is a way to search efficiently in an exponential search area.From self-tuning to self-designing information techniques
marvelous as the RocksDB effects may well be, the truth continues to be that the underlying information buildings don't seem to be altered: RocksDB is still a key-value keep.
DASlab's implementation works as an add-on layer on good of RocksDB. this residue inspects workloads and hardware configuration dynamically at run time, and makes use of records Calculator to find and practice the highest quality configuration.
This turned into a practical alternative made on the foundation of restricting the search house, as limiting oneself to key-price facts constructions makes things more manageable. The imaginative and prescient goes neatly past that besides the fact that children.
It sounds science-fiction like, however may well be closer than you consider: Harvard's DASlab is engaged on self-designing facts systems. photo: DASlab / Harvard
How about deciding on the type of equipment it truly is gold standard perfect to tackle workloads on a per-software groundwork? and not simply amongst latest programs, too.
wholly-fledged, this analysis could lead to personalized system design, tailored to the needs of selected applications. and those techniques would even be in a position to self-adapt at runtime, if the workloads change.
This may additionally sound like science fiction, and Idreos estimates it be at the least 10 years away. but it's smartly below method. beyond featuring this research on the world's most prestigious conferences, Idreos is additionally engaged on commercializing it, youngsters we are not at liberty to divulge particulars.computer gaining knowledge of, and figuring out what you're doing
statistics Calculator uses a hybrid method -- part analytical, part benchmarking, part computing device getting to know (ML). Idreos has been relying on analytical techniques for ages, and half-jokingly remarks that "ML is for if you happen to don't really know what you are doing."
but severely, when discussing the facts Calculator approach in comparison to Oracle, as an example, one evident query is what type of datasets Idreos' crew could maybe use.
As opposed to the Oracles of the realm, DASlab does not have entry to a whole lot precise-life database deployment operational statistics. Idreos notes besides the fact that children that for an excellent variety of issues, they know precisely what to do and the way, and their analytical fashions are enough:
if you happen to depend on ML solely, what you get is an approximate reply. but there are some decent explanation why we use it.
First, as a research system that can point in opposition t a fine answer. Then with our analytical model it all comes down to an equation that takes 1 micro-second to run, and we've the highest quality answer.
In our work for Key-price shops, the design space is massive, however we know it somewhat well. we've developed analytical fashions that work, so we do not actually need ML. (Generalized) information Calculator is different.
Idreos explains that they can't construct an analytical mannequin for each feasible facts constitution -- at least no longer at this element. The design area is dynamic, it be becoming, and or not it's challenging to pin down. What they do is that they include domain knowledge, corresponding to how access method primitives behave, and then synthesize an analytical mannequin equivalent.
as an instance, they model the habits of random access, scan, or binary bushes. Then they use this to synthesize more complicated constructions comparable to indexes.
additionally: what is laptop researching? every thing you should recognize
these analytical models should be slightly off, however, as they do not characterize the realm with 100% accuracy. In statistics buildings, says Idreos, what you usually miss might be some statistics or hardware houses.
DASlab makes use of ML to instruct algorithms according to analytical and benchmark consequences. they have an analytical model and run some benchmarks on certain data and configurations, and consequences are then fed to ML algorithms as training information.
This allows them to reply questions similar to "I need to run a scan on 5GB of data with those elements on this hardware, how lengthy will it take?", even without having built a specific analytical model for this.Zen and the art of facts structures
comparable to all ML strategies, selecting the best parameters to incorporate in these ML models is extraordinarily critical. during this case, it comes down to picking out the parameters that have an impact on hardware and utility configuration, even when not being certain exactly how.
For the subsequent levels of this analysis, Idreos envisions a layered ML strategy, according to reinforcement gaining knowledge of:
What we have built works like this: we input a design, and get a value as an output. here's comparable to ML labeling, in terms of labeling inputs. so that they can use our hybrid algorithm to label practicing records for yet another ML algorithm layer to get extra approximate solutions.
besides the fact that children the preliminary fruits of this analysis are already about to be commercialized, it may take a long time earlier than we see it unfold entirely.
Idreos, despite the fact, strategies this with a Zen form of perspective that makes one trust that self-designing information programs are extra or much less inevitable. appears like an extra enviornment of creativity prior to now reserved for people is en route to automation.
information is arguably the most useful device within the up to date enterprise arsenal, and its transformative nature is growing the need for overhaul at every level of enterprise operations. facts-powered improvements like synthetic intelligence and computer researching are using revolutionary technological developments all through the market and expanding the have an impact on data has on individual businesses, in addition to an increasingly cloud-linked community.
The amount of purchasable statistics and tempo of ecosystem expansion are developing limitless alternatives for growth however also new dangers as these transformations threaten to outpace the modernizations in security efforts essential to included efficiency. the prevailing safety tenet has lengthy been law via limit, but in a market so rooted in connectivity and accessibility, security needs a digital transformation of its own.
“As we circulation to a digital business the place the specific information and services associated with the statistics develop into the enterprise, you’re no longer talking about a way to avoid entry, you’re talking about how to correctly share entry,” referred to Barbara Kay (pictured), senior director of security product advertising at Extrahop Networks Inc.
A tech protection leader with event offering coverage through groups like McAfee Inc. and ExtraHop, Kay has guided businesses throughout the business’s evolving safety needs for over a decade. Now, she’s leveraging that abilities to radically change security via a data revolution.
Kay sat down with Peter Burris (@plburris) for a CUBEConversation at theCUBE’s studio in Palo Alto, California. (* Disclosure beneath.)
This week, theCUBE spotlights Suzanne Frey in our women in Tech feature.Reconsidering cybersecurity hazards
Kay turned into brought into ExtraHop as part of its transition from a community performance-centric business to one with a mission of optimizing in cybersecurity. while the company has been assisting shoppers of their protection wants for years, the market shifts round information brought about ExtraHop to take an lively method to protection innovation the use of the automation power and insights at its disposal.
“We knew how vital it become to aid the americans in the protection Operations group be greater advantageous, get to the basis trigger, and get on with existence extra at once,” Kay spoke of.
ExtraHop’s holistic protection method contains not handiest reactionary fixes, but preemptive solutions that beef up common statistics strategies. The significant expertise promised by using digital transformation comes with the chance of protection vulnerabilities, and the chance of breaches like those considered at Equifax Inc. and others looms over agencies desirous to modernize.
“We’ve considered the variety of scorched-earth attacks; all that stuff has americans in fact worried, and the network traffic zone is a neighborhood that has been underserved when it comes to safety hobby,” Kay said.
expanding digitization creates greater alternatives for breach, as does a community weakened via the many endpoints that allow the connectedness nowadays’s market depends on. no matter if internally or amongst outside companions, the business-essential facts that powers all methods ought to be included to make certain functionality and security right through the total network.
“It used to be that the model for protection became you loaded up your end aspect with a bunch of defenses, [but] so few gadgets now are able to be managed with an agent. that you could’t control these endpoints the equal way we used to. We must feel in another way in regards to the problem,” Kay stated.
Even 10 p.c extra facts accessibility may end up in a net salary enhance of $sixty five million for the ordinary Fortune 1000 company, however that accessibility can't come at the cost of openness to malware. “Your worker database, your customer database, the web server, the facts store, the app server — you want every thing to work collectively and dwell working. For these instruments to interact with things, they must use the network,” Kay mentioned.Automating records protection
with a view to fight these adapting threats, ExtraHop employs using investigative insights derived from the contextual information amassed by way of desktop getting to know. Metrics and metadata extracted from the community’s rich records is sent to the cloud, which then makes use of models that are designed for protection to extract behavioral implications.
“You have to be pondering concerning the nature of the interaction in place of the specific facts point. computing device getting to know is a fine approach to extrapolate and understand the bigger landscape of issues, and ExtraHop is hitching that computer gaining knowledge of engine to this wealthy source of contextual facts,” Kay mentioned.
This degree of insurance plan isn’t reserved for the enterprise, according to Kay. With organizations of all sizes working in the same community, even small to midsize agencies should take an aggressive method to optimizing protection.
“It isn’t necessarily about measurement; it’s about your perspective on protection. if your functions went down or your databases had been stolen, how crippling would that be for your company?” she asked.Enabling visibility for more advantageous believe
With a profession spanning over a decade, Kay is neatly-versed in the industry’s ever-altering cybersecurity needs. Kay’s event started with her consulting company comfortable through Design group, which she created to support information security corporations in increasing attain and superior helping consumers. before becoming a member of ExtraHop, Kay lead protection operations at McAfee and developed the company’s automatic security platform.
right through her career, Kay has labored to bridge gaps in each safety and conversation to create extra effective techniques between disparate community factions. At ExtraHop she’s working to get in entrance of the brand new concerns as a consequence of the trade’s information explosion, in addition to get to the bottom of the collaboration issues that stem from finger pointing following the discovery of security issues. whereas measures just like the 72-hour disclosure window mandated by the eu’s widely wide-spread records protection law are supposed to support in the resolution of a compromised information incident, Kay talked about that these subsequently damage typical safety efforts.
“Seventy-two hours isn't that plenty time when something definitely advanced has gone on. That’s why we see serial disclosure activities. Then anytime you ought to re-report your event, you degrade what little credibility you had. That’s in fact going to harm our industry,” she noted.
searching ahead, Kay is concentrated on growing enhanced average accountability tactics with a view to help corporations and purchasers feel at ease.
“[We’re] attempting to find a supply of certainty that means that you can [see] what’s in reality occurring. The sooner which you can try this and believe first rate in regards to the conclusion you obtained to, the more successful, the greater assured, and the greater equipped you are to stream forward,” she concluded.
Watch the finished video interview under, and make sure to take a look at more of SiliconANGLE’s and theCUBE’s cube Conversations. (* Disclosure: ExtraHop Networks, Inc. backed this segment of theCUBE. Neither Extrahop nor other sponsors have editorial control over content material on theCUBE or SiliconANGLE.)picture: SiliconANGLE for the reason that you’re right here …
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70-465 exam Dumps Source : Designing Database Solutions for Microsoft SQL Server
Test Code : 70-465
Test Name : Designing Database Solutions for Microsoft SQL Server
Vendor Name : Microsoft
Q&A : 111 Real Questions
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This handout photo taken from an helicopter and launched through the Vigili del Fuoco, the Italian firement, on Aug.. 6, 2018, suggests black smoke rising in the sky after a tanker exploded on the motorway close to the airport, in Bologna.
HANDOUT, AFP/Getty photographs
A tanker truck carrying flammable fabric exploded Monday within the Italian metropolis of Bologna, killing at the least two people and injuring up to 70 in a big fireball.
part of a highway collapsed after the explosion. The 60 to 70 accidents covered severe burns, in accordance with Italian police.
The truck turned into carrying liquefied petroleum gasoline, according to the ANSA news company, however authorities couldn’t ascertain the cloth.
"My vehicle remains beneath the flyover, i'm waiting to see if and when i will get it again," Marco Rosadini, from Arezzo, Italy, told ANSA. "At one point, we heard a violent explosion. i assumed it became an assault."
A police video showed the tanker failing to brake and plowing into the rear of a truck stopped in traffic, with flames exploding on affect. a different truck appeared to hit the tanker from at the back of.
Flames from the explosion spark off secondary blasts in a new automobile lot under, in response to the Italian television station Sky TG24.
a girl residing about two-thirds of a mile from the blast pointed out many residents had to depart due to the black smoke.
“i was in the apartment and i heard an incredible bang and screams from the window. I noticed an incredible plume of smoke,” Crisina Felicani instructed Sky TG24. “There changed into panic in the local, because it wasn’t clear what happened.”
Contributing: The linked Press
Copyright 2017 USATODAY.com
Larry Kucera, 66, of Grand Island, died Thursday, July 22, 2010, at St. Francis clinical center.
services could be at 2 p.m. Tuesday at all Faiths Funeral home.
There should be no visitation. Cremation has taken location.
extra particulars will appear later.
HARTFORD, CT — Connecticut scholar 2017-2018 SAT scores dipped a few facets in comparison to the previous 12 months in each English and math. The regular English language arts rating become 516 compared to 524 and the math ranking turned into 503 compared to 507. The maximum possible score in each area is 800.
State department of education officers talked about the mild drop is never statistically tremendous, in accordance with the Hartford Courant.
The state has used the SAT as its professional check evaluation for juniors in region of the Smarter Balanced evaluation Consortium or SBAC check.
take a look at the effects for all districts under.DistrictSubjectTotal variety of StudentsTotal number TestedAverage ScoreAchievement First Hartford Academy Inc. DistrictELA3636458Achievement First Hartford Academy Inc. DistrictMath3636453Amistad Academy DistrictELA5145522Amistad Academy DistrictMath5145481Ansonia college DistrictELA150148488Ansonia school DistrictMath150148460Area Cooperative tutorial ServicesELA2013*area Cooperative tutorial ServicesMath2013*Avon faculty DistrictELA226218602Avon school DistrictMath226218594Berlin faculty DistrictELA232231547Berlin college DistrictMath232231537Bethel faculty DistrictELA233230533Bethel school DistrictMath233230516Bloomfield college DistrictELA156152491Bloomfield school DistrictMath156152461Bolton college DistrictELA6767531Bolton school DistrictMath6767519Branford school DistrictELA225217511Branford school DistrictMath225217503Bridgeport success First DistrictELA5345510Bridgeport fulfillment First DistrictMath5345490Bridgeport college DistrictELA12181052441Bridgeport faculty DistrictMath12181052428Bristol faculty DistrictELA594566492Bristol school DistrictMath594566478Brookfield faculty DistrictELA217209557Brookfield school DistrictMath217209544Brooklyn faculty DistrictELA***Brooklyn faculty DistrictMath***Canton college DistrictELA120117587Canton college DistrictMath120117561Capital Preparatory Harbor faculty Inc. DistrictELA3129463Capital Preparatory Harbor faculty Inc. DistrictMath3129449Capitol location schooling CouncilELA523488492Capitol region education CouncilMath523488468Cheshire faculty DistrictELA375358555Cheshire college DistrictMath375358549Clinton faculty DistrictELA141138530Clinton college DistrictMath141138501Colchester school DistrictELA191183538Colchester school DistrictMath191183515Columbia college DistrictELA***Columbia faculty DistrictMath***normal ground excessive college DistrictELA4645499Common ground excessive college DistrictMath4645467Connecticut Technical training and profession SystemELA24352388456Connecticut Technical schooling and profession SystemMath24352388445Cooperative educational ServicesELA2018*Cooperative tutorial ServicesMath2018*Coventry faculty DistrictELA104104530Coventry school DistrictMath104104518Cromwell college DistrictELA132126525Cromwell school DistrictMath132126504Danbury college DistrictELA686662480Danbury faculty DistrictMath686662460Darien college DistrictELA339306601Darien college DistrictMath339306605Derby college DistrictELA7066471Derby college DistrictMath7066438East Granby college DistrictELA7373550East Granby faculty DistrictMath7373531East Haddam faculty DistrictELA7471534East Haddam college DistrictMath7471507East Hampton college DistrictELA130127540East Hampton college DistrictMath130127524East Hartford school DistrictELA530503471East Hartford school DistrictMath530503451East Haven faculty DistrictELA210197479East Haven college DistrictMath210197458East Lyme faculty DistrictELA254246546East Lyme college DistrictMath254246540East Windsor faculty DistrictELA6765471East Windsor college DistrictMath6765460Eastern Connecticut Regional academic service center (EASTCONN)ELA8070465Eastern Connecticut Regional academic service core (EASTCONN)Math8070431EdAdvanceELA86*EdAdvanceMath86*Ellington college DistrictELA199196536Ellington college DistrictMath199196528Elm metropolis school Preparatory school DistrictELA2928506Elm metropolis college Preparatory school DistrictMath2928492Enfield school DistrictELA311306509Enfield faculty DistrictMath311306490Explorations DistrictELA2424480Explorations DistrictMath2424432Fairfield college DistrictELA778762570Fairfield school DistrictMath778762556Farmington college DistrictELA289284583Farmington school DistrictMath289284582Glastonbury faculty DistrictELA507501571Glastonbury school DistrictMath507501578Granby school DistrictELA176173561Granby faculty DistrictMath176173549Greenwich school DistrictELA685657591Greenwich school DistrictMath685657589Griswold school DistrictELA134125487Griswold school DistrictMath134125478Groton college DistrictELA273251514Groton faculty DistrictMath273251501Guilford faculty DistrictELA269268589Guilford school DistrictMath269268573Hamden faculty DistrictELA363341497Hamden school DistrictMath363341473Hartford college DistrictELA12271085448Hartford school DistrictMath12271085438Highville constitution school DistrictELA1514*Highville charter school DistrictMath1514*Jumoke Academy DistrictELA1512*Jumoke Academy DistrictMath1512*Killingly faculty DistrictELA193182506Killingly school DistrictMath193182477LearnELA205199510LearnMath205199486Lebanon school DistrictELA9291522Lebanon college DistrictMath9291519Ledyard school DistrictELA192186537Ledyard school DistrictMath192186517Litchfield faculty DistrictELA7271551Litchfield school DistrictMath7271527Madison faculty DistrictELA272263593Madison school DistrictMath272263582Manchester faculty DistrictELA432389483Manchester faculty DistrictMath432389468Meriden faculty DistrictELA514471470Meriden college DistrictMath514471437Middletown college DistrictELA325302485Middletown school DistrictMath325302470Milford faculty DistrictELA435424529Milford school DistrictMath435424521Monroe faculty DistrictELA247237569Monroe faculty DistrictMath247237553Montville school DistrictELA146140515Montville school DistrictMath146140500Naugatuck college DistrictELA296270483Naugatuck school DistrictMath296270456New Britain college DistrictELA611535433New Britain college DistrictMath611535417New Canaan school DistrictELA312302604New Canaan college DistrictMath312302604New Fairfield school DistrictELA221216563New Fairfield college DistrictMath221216542New Haven school DistrictELA12791169458New Haven school DistrictMath12791169439New London faculty DistrictELA248233454New London college DistrictMath248233446New Milford college DistrictELA307288542New Milford college DistrictMath307288518Newington school DistrictELA319311539Newington school DistrictMath319311530Newtown school DistrictELA409392557Newtown faculty DistrictMath409392556North Branford school DistrictELA130128516North Branford college DistrictMath130128493North Haven college DistrictELA250247533North Haven college DistrictMath250247520North Stonington faculty DistrictELA4240502North Stonington faculty DistrictMath4240495Norwalk school DistrictELA833797489Norwalk college DistrictMath833797478Norwich Free Academy DistrictELA552529496Norwich Free Academy DistrictMath552529488Norwich college DistrictELA1514*Norwich faculty DistrictMath1514*historical Saybrook faculty DistrictELA109104578Old Saybrook faculty DistrictMath109104564Oxford faculty DistrictELA159156536Oxford college DistrictMath159156519Path Academy DistrictELA2411*course Academy DistrictMath2411*Plainfield faculty DistrictELA163148489Plainfield faculty DistrictMath163148462Plainville school DistrictELA180174512Plainville faculty DistrictMath180174507Plymouth college DistrictELA126122501Plymouth college DistrictMath126122501Portland college DistrictELA102102552Portland college DistrictMath102102543Putnam college DistrictELA7874478Putnam school DistrictMath7874458Regional college District 01ELA111107524Regional faculty District 01Math111107493Regional faculty District 04ELA144138559Regional faculty District 04Math144138522Regional school District 05ELA361356582Regional faculty District 05Math361356575Regional college District 06ELA8884543Regional faculty District 06Math8884499Regional faculty District 07ELA198194563Regional school District 07Math198194556Regional school District 08ELA230222571Regional faculty District 08Math230222574Regional faculty District 09ELA231223581Regional college District 09Math231223575Regional faculty District 10ELA190189569Regional college District 10Math190189561Regional college District 11ELA4141499Regional college District 11Math4141490Regional faculty District 12ELA6767530Regional school District 12Math6767528Regional faculty District 13ELA138135553Regional college District 13Math138135522Regional school District 14ELA193190525Regional school District 14Math193190517Regional school District 15ELA304297564Regional school District 15Math304297559Regional school District 16ELA167163539Regional school District 16Math167163523Regional school District 17ELA165164570Regional faculty District 17Math165164543Regional faculty District 18ELA116109577Regional faculty District 18Math116109564Regional faculty District 19ELA288256552Regional school District 19Math288256547Ridgefield college DistrictELA404383598Ridgefield college DistrictMath404383593Rocky Hill college DistrictELA182181537Rocky Hill faculty DistrictMath182181525Salem school DistrictELA***Salem school DistrictMath***Seymour college DistrictELA166161530Seymour faculty DistrictMath166161513Shelton school DistrictELA356346536Shelton college DistrictMath356346527Simsbury school DistrictELA358344603Simsbury school DistrictMath358344592Somers faculty DistrictELA124124523Somers school DistrictMath124124518South Windsor school DistrictELA321317545South Windsor faculty DistrictMath321317533Southington faculty DistrictELA464448535Southington faculty DistrictMath464448521Sprague college DistrictELA***Sprague school DistrictMath***Stafford school DistrictELA9389506Stafford school DistrictMath9389497Stamford Academy DistrictELA4132380Stamford Academy DistrictMath4132377Stamford faculty DistrictELA10931032496Stamford college DistrictMath10931032488Stonington college DistrictELA175163539Stonington faculty DistrictMath175163532Stratford school DistrictELA489469482Stratford faculty DistrictMath489469473Suffield college DistrictELA215213560Suffield college DistrictMath215213547The Bridge Academy DistrictELA3434462The Bridge Academy DistrictMath3434438The Gilbert college DistrictELA121117489The Gilbert faculty DistrictMath121117512Thomaston school DistrictELA6968543Thomaston school DistrictMath6968519Thompson faculty DistrictELA6965496Thompson college DistrictMath6965484Tolland school DistrictELA197194564Tolland college DistrictMath197194569Torrington school DistrictELA196191475Torrington faculty DistrictMath196191468Trumbull faculty DistrictELA526515564Trumbull college DistrictMath526515565Unified faculty District #2ELA1614*Unified college District #2Math1614*Vernon college DistrictELA203191513Vernon college DistrictMath203191488Voluntown faculty DistrictELA***Voluntown college DistrictMath***Wallingford faculty DistrictELA460446518Wallingford school DistrictMath460446504Waterbury school DistrictELA11611068436Waterbury college DistrictMath11611068419Waterford school DistrictELA193191537Waterford school DistrictMath193191525Watertown college DistrictELA214208512Watertown faculty DistrictMath214208482West Hartford faculty DistrictELA766749570West Hartford faculty DistrictMath766749559West Haven faculty DistrictELA371338469West Haven faculty DistrictMath371338447Westbrook college DistrictELA5956552Westbrook faculty DistrictMath5956537Weston faculty DistrictELA211205608Weston faculty DistrictMath211205598Westport faculty DistrictELA485477609Westport faculty DistrictMath485477609Wethersfield college DistrictELA290282524Wethersfield faculty DistrictMath290282510Wilton college DistrictELA326317601Wilton college DistrictMath326317591Winchester college DistrictELA***Winchester college DistrictMath***Windham college DistrictELA128118427Windham school DistrictMath128118416Windsor Locks college DistrictELA115114506Windsor Locks college DistrictMath115114491Windsor faculty DistrictELA279265503Windsor school DistrictMath279265482Wolcott faculty DistrictELA202198512Wolcott college DistrictMath202198500Woodstock Academy DistrictELA299297536Woodstock Academy DistrictMath299297531Woodstock faculty DistrictELA***Woodstock faculty DistrictMath***
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