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Test Number : A00-204
Test Name : Sas warehouse architect concepts
Vendor Name : SASInstitute
Q&A : 65 Dumps Questions

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Sas warehouse architect concepts education

How up to date company intelligence shapes up to huge facts | A00-204 Dumps and Real exam Questions with VCE Practice Test

How have company business intelligence (BI) innovations advanced in fresh years within the face of big statistics? Have businesses and other organisations changed their BI tool choices and the ways they set up their teams and technical architectures as facts volumes have expanded and become much less structured, greater “messy”?

right here, we first get a CEO-stage point of view from two founder-executives at opposite ends of the spectrum of opinion, then some tips from an analyst standpoint, followed by means of testimony from three user companies: constructing society Nationwide, funding administration enterprise Schroders and games enterprise King.

Three waves of BI or startup special pleading?

Frank Bien, CEO of enterprise intelligence platform corporation Looker, laid out the thesis of his business to computing device Weekly in 2017, contending that the rise of Hadoop and NoSQL databases had outdated prior generations of BI expertise.

Bien’s narrative of business intelligence involves three waves of BI. the first changed into the big monolithic stacks: enterprise Objects, Cognos and Microstrategy. “What you bought there were finished techniques – and also you spent lots of time ‘manicuring the lawn’. by that I imply databases had been slow, and had been built to do transactions, not analytics. if you desired to ask a question, you had to reorganise the facts physically,” he says. And that, he continues, grew to be inflexible and inflexible.

The 2d section become one in all “blowing up that stack”, about seven years in the past. “there have been small equipment raining out of the sky to do issues one at a time, like information guidance or visualisation. And, as companies, we observed to purchasers: ‘you set all that collectively’,” he says. This, in his view, changed into the era of Qlik and Tableau.

“at the identical time, there became a revolution in facts infrastructure, with technologies popping out of Google, fb and the like. Then the cloud happened, with Amazon Redshift, Microsoft Azure, and the like, and it grew to become trivial to shop everything. So, that 2nd wave of BI equipment become evolving while there become an entire revolution underneath it, and the equipment didn't capture up,” says Bien.

“And so there is a 3rd wave, where there is a reconstitution of a complete platform, but working during this new records world,” he adds. Which is the place, in Bien’s view, Looker is available in.

Michael Saylor, CEO and founder of one of the most dependent enterprise intelligence enterprises, Microstrategy, disagrees with this evaluation. In an interview with computing device Weekly in 2017, he countered: “I think any startup wants a narrative. It is right that there are levels, and businesses need to grow and evolve or they get left at the back of. but a more beneficial metaphor is that of an increasing universe. the world is not transferring from relational to huge facts, it's expanding in distinctive dimensions simultaneously.

“You still see lots of Oracle, SQL and Teradata. There are MDX language sources – OLAP cubes. And there are the Hadoop distributions. these are three information systems, and no one of them is going to make the others go away. which you could go to the proper 5,000 organizations on the earth and locate they are the use of them all.

“And it goes on. There are functions like Salesforce, Workday, SAP, etc – americans will need to question the facts in those without delay. And there are internet sources. None of those will exchange each other, both. It’s extra doubtless that a Coca-Cola will need to be a part of information in Hadoop, Salesforce and Oracle,” he pointed out.

“Now that you could build a small or mid-sized enterprise solving a subset of the statistics problem. each enterprise has to make a decision where to make its investments. Some BI enterprise may come alongside and say, ‘we are the choicest for the Hortonworks distribution of Hadoop’, and that may fly for a while. but I have been during this enterprise for 27 years, and each three years there's a new facts expertise which is the fad.”

Complexity, complexity, they’ve all acquired complexity

So, what's the state of play now, in 2019? Mike Ferguson, one of the crucial high-profile unbiased analysts within the box, takes the view that the records and enterprise intelligence complications colossal corporations, specifically, have today are much less about BI tooling choices and greater about records integration. a lot extra. The leading issue organizations – and other enormous companies – face, he says, is complexity.

“developing a data-pushed corporation is extra intricate than individuals believe. I always go returned to that Peter Drucker comment, ‘subculture eats strategy for breakfast’. it's more convenient with SMEs [small to medium-sized enterprises], but if a larger corporation has no chief information officer (CDO), or equivalent, you get lack of organisational alignment,” he says.

“corporations which might be doing smartly are strongly led by way of their CEOs, and definitely clear in regards to the priority to be given to information. The difficulty all the time looks to lie within the center, with the cultural issues of americans and approaches,” adds Ferguson.

“The objective isn't to prepare all information for all users, however to incrementally build up a set of capable-made datasets that people can decide on up and re-use” Mike Ferguson, unbiased analyst

In technical architecture phrases, he says the theory that organizations should deliver all their information to at least one Hadoop equipment, in a centralised data lake, could be feasible for mid-sized agencies, but there is such a deluge of facts now – computing device records, cyber web of things (IoT) data, social network records, open executive information, statistics from commercial suppliers – it's difficult to integrate.

“in all places you seem, there are disconnected swimming pools of information [in corporate organisations]. and you think, ‘could you now not just do this as soon as, and then we might all re-use it?’. So the objective is not to prepare all information for all users, however to incrementally build up a set of in a position-made datasets that people can prefer up and re-use. There are large companies very drawn to this. And so that you would have a group of statistics shops committed to ingestion, a group committed to cleaning and preparing stuff, and a gaggle maintaining relied on stuff,” says Ferguson.

As for enterprise intelligence utility, he says it is being “swamped by way of facts science”, pushed to at least one side with the aid of the now extra fashionable subject matter.

“I consider the difficulty here is twofold. BI has been advancing within the sort of artificial intelligence going into the equipment themselves to enrich productiveness. Say, recommending you to click on the appropriate visualisation for the problem you’re making an attempt to solve. The other being simplified interplay with these tools, with natural language processing and chatbot interfaces. but the problem in time-honored with BI is it’s being swamped through so a whole lot cash going into facts science equipment,” says Ferguson.

“and there's a conflict going on with the cloud carriers trying to get people onto their computing device learning-based mostly services for analytics. So it's a very fractured world, with BI left to at least one side a bit. additionally, talents are too thinly spread throughout too many records science technologies. it's chaotic.

“the combination of BI with deployed models from facts science is a big enviornment where americans want to see integration – with predictions, signals, forecasts and suggestions made easy to access. And BI providers who center of attention on that kind of component will support,” he says.

‘healthy to fly’ at Nationwide

How are company organisations rendering this complexity tractable, by the use of aligning and streamlining their information and analytics options?

Paul French, director of business intelligence, visualisation and reporting, facts and analytics, at constructing society Nationwide, defined his company’s method in a briefing with desktop Weekly on the Gartner statistics & Analytics conference in London earlier this yr.

in part, Nationwide’s method was recommended by the way airline pilots are organized to be “fit to fly” – a process French’s personal stepson has currently gone through. You don’t just climb into the cockpit of a jet and press “Go”.

French described how the constructing society has centralised its facts group, under a mandate from CEO Joe Garner, appointed in July 2016. French experiences to CDO Lee Raybould. Garner is aiming, says French, to circulate the society from a hierarchical, precise-down lifestyle to a extra “dependable freedom” atmosphere.

“From an information viewpoint, that has been ultimate, when it comes to assisting that shift by altering our data subculture,” he says. “if you desire people to be in a position to make selections all over the corporation in a spirit of responsible freedom, then empowering them with the appropriate information, and the correct ranges of self assurance in literacy, is a must have. basically, we are moving from being records restricted to being facts enabled.”

As part of that, Nationwide centralised its statistics governance, company intelligence, records warehousing and information lakes, and records science body of workers into one crew – right now of one hundred eighty americans, however recruiting to expand to round 300 in the close future – reporting to the CDO feature inaugurated by using the society’s CEO.

That central facts characteristic discovered that fifty% of the staff at Nationwide were spending the majority of their time on records education work.

“Our largest problem turned into we had Excel all over the place, entry all over, and SAS being used for the incorrect issues. SAS is a really terrific product when used for the right component, however it turned into getting used for loads of the inaccurate things – and understandably, because the company teams that had been constructing stuff in SAS had been not getting a imperative carrier from the information or IT teams. in order that they found a way, with tools that have been available to them. however we're in a spot now the place we deserve to have enhanced governance and manage, whereas enabling self-provider,” says French.

“virtually, we now have a imperative information science group that both develops superior analytics fashions to aid the enterprise, but also helps grow capacity and greatest apply in groups throughout the society. We function a hub and spoke mannequin that capability we advantage from a central group using most appropriate practice, standards, capacity building, expertise advancement and focusing on the massive, business-large opportunities, coupled with spoke groups in areas similar to advertising and risk which have area expertise in their company areas.”

He offers an instance of how SAS certainly is now getting used. SAS visible text Analytics permits the company to experiment with natural language processing. here is assisting to determine if it could stronger take into account the root cause of consumer contact through browser-primarily based messages from inside its internet bank channel, to provider contributors improved.

“We’ve more than a few these sorts of opportunities, the place we're exploring where richer amounts of data, advances in facts science and analytics technologies, and a strong funding in our americans – all part of our D&A [data and analytics] approach – are enabling us to continue to increase the carrier providing to our individuals,” says French.

From a technology structure standpoint, the Nationwide records stack comprises a Teradata information warehouse equipment with a Hortonworks Hadoop records lake connected to it. earlier than it decided on that warehouse and lake setup, it had Microsoft SQL Server cases unfold through the organization, he says.

“we're exploring the place richer amounts of records, advances in records science and analytics technologies, and a robust funding in our americans are enabling us to continue to Excellerate the carrier offering to our participants”

Paul French, Nationwide

On the BI side, Nationwide has taken a multi-service provider approach. “I’m of the view that there isn't any single BI device that takes care of all our use circumstances. we now have SAP enterprise Objects for extremely structured, static reporting, and have had for 10 years. We use QlikView for our dashboarding and guided statistics discovery, and have signed a licence for [the more advanced] QlikSense for up to five,000 clients,” says French.

Qlik changed into in the beginning a departmental answer for the commercial crew round 10 years in the past, and it has accelerated Qlik use based on the greater fresh wave of records and analytics strategy during the past three years.

Nationwide also uses ThoughtSpot – a search-based mostly BI device requiring little training – in the palms of its entrance-line personnel. “My view is 75% to eighty% of people in any company need elementary advice in an easy, intuitive method. ThoughtSpot gives a herbal language-based interface so that you can get someone, in a branch or contact centre, up and running with in half an hour’s practicing,” he says.

however the BI tooling is, he adds, a small piece of the puzzle in comparison with changing the facts lifestyle, which it has been doing with hobbies like information pace courting – where workforce from outdoor the facts crew can have time with statistics practitioners – and, most these days, its first hackathon. This, he says, was backed through someone who leads the contact centre change crew and became organised around an easy query: what is the have an impact on when a member contacts us by way of the cellphone?

Some 270 people received thinking within the four-week (dispersed in time and area) hackathon, working with Cisco call records, ranging in personnel from information science modelling teams to a local manager. “It’s really engaged people, and has begun proposing insight on a business enviornment we are interested in,” he says. And using, it looks, precisely the “messy” variety of statistics that lies beyond the numbers sitting within the neat rows and columns of a relational database – during this case, audio.

Schroders freeing company users to resolve own problems

Asset administration firm Schroders, deploy in 1804, is a further financial capabilities company that has been modernising its information and analytics approach. Whereas Nationwide is a Qlik customer, Schroders is an aficionado of its close rival, Tableau.

Mike Renwick, head of records and insights know-how at Schroders, offers this account of the issue the firm was attempting to resolve when, 4 years ago, it went looking for whatever thing like the Seattle-based mostly facts visualisation utility organisation’s wares.

“Tableau, for us, changed into always about increasing the floor enviornment of people who were in a position to resolve their personal problems in the line of enterprise, with information and help,” he tells computing device Weekly. “in the past, expertise groups tended to hold the monopoly for constructing reporting, and the tight interplay required made it intricate for business users to get to the element the place they were genuinely asking and answering questions of records.

“there is an interpretation layer between requirements gathering and implementation that intended the individuals who best understood the facts were having to ask others who understood the expertise greater to do it for them. Tableau shortens that distance and capability a finance group can without delay interrogate the facts themselves with their personal facts capabilities, to locate answers to questions in the second.”

Does he think older BI tools that classically matched up with information warehousing aren't such an excellent healthy for huge, unstructured or less structured facts?

“I suppose they occasionally will also be a great fit, despite the fact there is really a gap in person-friendly processing of unstructured statistics for consumption in a BI tool. Unstructured statistics needs some kind of structuring to be usefully processed – if in case you have your e mail inbox as an information source, you could possibly should turn it into some sort of structured form to make use of the facts,” says Renwick.

“Tableau is fairly unique, due to its internet facts connector concept – anything somewhat basic that lets you write an adaptor from some unstructured supply, for example, into structured Tableau statistics,” he provides.

“Kalpana Chari, skill lead of the competencies Analytics crew at Schroders, and her group used this to construct a connector to ElasticSearch, that allowed our users to seek certain terms acting in assembly notes, and then see how they style on a graph – consider Google trends for inner meeting notes. The outcomes is visualised in Tableau, and these entry elements into the ecosystem supposed it could be extended for this variety of use-case,” says Renwick.

“Our engineers and scientists work intently collectively. Our engineers do a superb job of building effective equipment and thinking concerning the entire gadget. This offers our data scientists greater time to answer complicated questions, discover exciting data and observe scientific rigour to company decisions”

Mike Renwick, Schroders

Describing how the ordinary facts and analytics programme is organised at Schroders and the way it has install its statistics engineers and scientists to work collectively, he says the statistics science team – the facts Insights Unit – tends to be interested in different types of expertise to those used in core programs in the business.

“because of their entertaining requirements, they aid to shift present thinking around records expertise against greater scalable and open models,” says Renwick. “In corporations like ours, which sell to other organizations instead of consumers, it’s no longer ordinary to come across datasets with billions of rows of statistics. youngsters, our data scientists are sometimes dealing with datasets coming near a hundred billion rows. This capacity common facts evaluation strategies can’t be used and the abilities of a pc programmer and statistician are vital, in addition to access to the massive records or cloud technologies to deal with data of this quantity.

“Our engineers and scientists work intently together, using their diverse and complementary skills in partnership. Our engineers do an excellent job of building powerful tools and thinking about the total equipment. This ends up in our information scientists being able to spend more time answering problematic questions, exploring enjoyable data and making use of scientific rigour to business selections for the complete enterprise,” he says.

And on the question of even if its efforts are centralised, decentralised or a bit of each, Renwick confirms it is a “little bit of both”.

“We see a crucial core of experts as a helpful starting element, however have made a point of each connecting to inside initiatives that in a innovative organisation can, and may, be somewhat emergent and seeding teams with embedded facts gurus – consider of them like field operatives who get deeply engrossed in particular enterprise strains, however improvement from the broader community of information science and engineering certified in other areas. creating some stream here is advantageous – jobs in-situ can develop into repetitive after a few years, so having a joined-up ecosystem of this neighborhood allows for people to rotate or specialise, or indeed, generalise.

On the proper-stage business advantages of its use of Tableau, visible at board level, Renwick says it has proved that it has delivered an eight times return on the fees.

“One story involved our investment operations guide crew that use Tableau dashboards they developed to examine data excellent ahead of trading. it is a secular-sounding use-case, but has a materially nice influence, decreasing error and omissions and with backside-line affect,” he says.

A BI strategy is more than an inventory of tools

whereas Nationwide, Schroders and King (see container under) all boast clear information and analytics concepts, Andy Bitterer, now an “evangelist” at SAP, but a protracted-time facts and BI-focused analyst, together with at Gartner, thinks this is all too exclusive.

talking on the co-discovered commercial enterprise information and enterprise Intelligence & Analytics conferences in November 2018, he referred to: “In my previous role at Gartner, we used to run an annual survey among three,000 or so CIOs worldwide. we would ask them what their most important pursuits had been for the subsequent 365 days, and company analytics become at all times near the top or appropriate. you could consider that if that turned into the case, you could possibly have a technique round that. but when you ask them about their BI strategy, they always discuss reporting, which gained’t get you to digital transformation.

“A BI strategy isn't just a list of the tools that we are looking to have. many times I actually have asked users, ‘What’s your BI method?’, and they have responded with the identify of a supplier. That’s not a methodology. That’s like Ferrari asserting, ‘Our formula 1 racing approach is we’re going to make use of red paint, Bridgestone tyres and Esso fuel, and drive in fact quickly in a circle’.” 


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