Blogs

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Data Management

Blend, cleanse and prepare data for analytics, reporting or data modernization efforts

Data Management

Joyce Norris-MontanariOctober 9, 2015 0

Data integration methods

There are many ways to do data integration. Those include: Extract, transform and load (ETL) – which moves and transforms data (with some redundancy) from a source to a target. While ETL can be implemented (somewhat) in real time, it is usually executed at intervals (15 minutes, 30 minutes, 1

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Data Management

mature businesswoman considers two different types of MDM

Jim HarrisOctober 7, 2015 0

Big data quality – Part 1

Jim Harris addresses some of the most common questions and challenges big data poses for data quality.

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Data Management

Phil SimonOctober 2, 2015 0

Overcoming the IT-Business Divide in an era of big data, Part 3

.@philsimon on bridging the IT-business divide once and for all.

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Data Management

Dr. Laurie MilesOctober 1, 2015 0

Three tips for building a data scientist team

If I were to believe the feedback I get, statisticians are among the most difficult people to work with. What’s more, they’re the only group that should be allowed to work in data analytics. It sounds harsh, but this may explain why big data projects continually fail. Businesses need statisticians who are both

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Data Management

Matthew MagneSeptember 29, 2015 0

SAS Data Management helps organizations boldly go where no one has gone before

As a youngster in the 70s and 80s, Star Trek inspired my imagination and fostered a great love for science, technology and reading. (See the embedded Star Trek infographic for some interesting factoids – did you know that there were 28 crew member deaths by those wearing red shirts?) Captain Kirk and the

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Data Management | Internet of Things

IoT in Transportation

Lee Ann DietzSeptember 28, 2015 0

Transporting analytics to the Internet of Things

Why are so many companies across a diverse set of industries investing in and around the Internet of Things? Everywhere I go, every blog I read … I sound like my favorite band from the 80s: the Internet of Things is watching me. In reality, it’s the reverse: I'm seeing

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Data Management

Brad SitlerSeptember 25, 2015 0

The top 10 use cases for analytics in high-growth health technologies

Healthcare IT News recently published an article on 18 health technologies poised for big growth, a list culled from a HIMSS database. The database is used to track an extensive list of technology products that have seen growth of 4-10 percent since 2010, but have not yet reached a 70

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Data Management

Arun C. MurthySeptember 24, 2015 0

Apache YARN to become “the operating system for your data”

It’s been an amazing journey with Hadoop. As we discussed in an earlier blog, Hadoop is informing the basis of a comprehensive data enterprise platform that can power an ecosystem of analytic applications to uncover rich insights on large sets of data. With YARN (Yet Another Resource Negotiator) as its

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Data Management

Phil SimonSeptember 23, 2015 0

Overcoming the IT-Business divide in an era of big data, Part 2

.@philsimon on the new role of IT.

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Data Management

Brooke FortsonSeptember 22, 2015 0

Meet your SAS #StrataHadoop Team: Derek Hardison

A week from today, we'll be in New York City for Strata + Hadoop World, where we’ll kick things off at the Opening Reception. Be sure to stop by booth 543 to meet the team IRL (in real life)! They are excited about the event and eager to talk with attendees.

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Data Management

Stuart RoseSeptember 22, 2015 0

The final countdown… and beyond

It’s rather appropriate that the rock band Europe recorded the hit “The Final Countdown”, because today, September 22nd, represents 100 days until the much anticipated (and delayed) European insurance legislation Solvency II will come into effect on January 1st 2016. Designed to introduce a harmonized, EU-wide insurance regulation, Solvency II

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Data Management

Phil SimonSeptember 21, 2015 0

Overcoming the IT-Business Divide in an era of big data, Part 1

.@philsimon on the new challenges of an old problem.

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Data Management

Brooke FortsonSeptember 18, 2015 0

Meet your SAS #StrataHadoop Team: Dan Zaratsian

It’s me again!! We're at the halfway point of meeting our Strata + Hadoop World dream team. So far, you’ve met machine learning guru Patrick Hall; data management expert Clark Bradley; and advanced analytics specialist Rachel Hawley. Next up … Dan Zaratsian! I met Dan a few years back while preparing for Analytics 2013

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Data Management

Dylan JonesSeptember 16, 2015 0

Big data integration - A good starting point for data governance?

In the UK, technology trends move a little slower than for our US counterparts. It was about 5 years ago when I first met a data leader at a conference on this side of the pond who was actively engaging in large scale big data projects. This wasn’t a presenter

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Data Management

Joyce Norris-MontanariSeptember 14, 2015 0

Data integration – Job skills required for success

Data integration, on any project, can be very complex – and it requires a tremendous amount of detail. The person I would pick for my data integration team would have the following skills and characteristics: Has an enterprise perspective of data integration, data quality and extraction, transformation and load (ETL): Understands

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Data Management

Brooke FortsonSeptember 11, 2015 0

Meet your SAS #StrataHadoop Team: Clark Bradley

Meet Clark Bradley: SAS technical architect by day and comedian by night. When he’s not demoing SAS Data Loader for Hadoop, he’s blogging about it on The Data Roundtable. Clark and a core SAS team of thought leaders, developers and executives will be in New York City on September 29 at Strata

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Data Management

David LoshinSeptember 8, 2015 0

Big data modeling: An iterative approach - Part 1

In my prior two posts, I explored some of the issues associated with data integration for big data and particularly, the conceptual data lake in which source data sets are accumulated and stored, awaiting access from interested data consumers. One of the distinctive features of this approach is the transition

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Customer Intelligence | Data Management

Kelly McGuireSeptember 4, 2015 0

Back to the Basics Part One: An analytics primer for hoteliers

with Natalie Osborn, Senior Industry Consultant, Hospitality and Gaming Practice, SAS. It’s back to school time, and back to school reminds me of getting back to the basics. So, we thought we’d start the fall with a “back to the basics” refresher series on analytics. To accomplish this, Natalie and

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Data Management

Georgia MarianiSeptember 3, 2015 0

Education Meets Big Data: The benefits of an SLDS

This is my final entry in the Education Meets Big Data blog series. Let’s review what we've covered so far… In my first post, I explained that statewide longitudinal data systems (SLDSs) track student data from preschool through college and workforce across the state. SLDSs can be used to see one

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Data Management

Jim HarrisSeptember 2, 2015 0

Tips for successful big data integration

Integrating big data into existing data management processes and programs has become something of a siren call for organizations on the odyssey to become 21st century data-driven enterprises. To help save some lost time, this post offers a few tips for successful big data integration.

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Data Management

Jim HarrisAugust 31, 2015 0

Data quality to "DI" for

There is a time and a place for everything, but the time and place for data quality (DQ) in data integration (DI) efforts always seems like a thing everyone’s not quite sure about. I have previously blogged about the dangers of waiting until the middle of DI to consider, or become forced

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Data Management

Phil SimonAugust 26, 2015 0

Data integration: Comparing traditional sources and big data

While not on the same level of Rush, I do fancy myself a fan of The Who. I'm particularly fond of the band's 1973 epic, Quadrophenia. From the track "5:15": Inside outside, leave me alone Inside outside, nowhere is home Inside outside, where have I been? The inside-outside distinction is rather apropos

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Data Management

David LoshinAugust 24, 2015 0

Data integration considerations for the data lake: Standardization and transformation

In my last post, I noted that the flexibility provided by the concept of the schema-on-read paradigm that is typical of a data lake had to be tempered with the use of a metadata repository so that anyone wanting to use that data could figure out what was really in

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Data Management

Jim HarrisAugust 20, 2015 0

Data governance and analytics

The intersection of data governance and analytics doesn’t seem to get discussed as often as its intersection with data management, where data governance provides the guiding principles and context-specific policies that frame the processes and procedures of data management. The reason for this is not, as some may want to

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Data Management

Georgia MarianiAugust 20, 2015 0

Education meets big data: key steps in preparing for your SLDS

In my first blog post in the Education meets Big Data blog series, I explained the need for Statewide Longitudinal Data Systems(SLDS). In the blog post following, I shared an interview with Armistead Sapp, one of the authors of the book, "Implement, Improve and Expand Your Statewide Longitudinal Data System." In this

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Data Management

Phil SimonAugust 19, 2015 0

Big data integration: The case against an "all-in" approach

I've spent a great deal of time in my consulting career railing against multiple systems of record, data silos and disparate versions of the truth. In the mid-1990s, I realized that Excel could only do so much. To quickly identify and ultimately ameliorate thorny data issues, I had to up

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Data Management

Matthew MagneAugust 18, 2015 0

What do metadata bridges, HAWQ and gender analysis have in common?

Now that another summer of 12-hour family road-trips to Maine and Ohio, pricey engineering and basketball camps for the kids, and beating the heat at the beach are over, I've taken a fresh look at what people are focused on with their data – and what SAS is providing in the data management space.

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Data Management | Fraud & Security Intelligence

Stuart RoseAugust 13, 2015 0

Is good…good enough?

“Garbage in, garbage out” is more than a catchphrase – it’s the unfortunate reality in many analytics initiatives. For most analytical applications, the biggest problem lies not in the predictive modeling, but in gathering and preparing data for analysis. When the analytics seems to be underperforming, the problem almost invariably

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Data Management

David LoshinAugust 12, 2015 0

Data integration considerations for the data lake: The need for metadata

A few of our clients are exploring the use of a data lake as both a landing pad and a repository for collection of enterprise data sets. However, after probing a little bit about what they expected to do with this data lake, I found that the simple use of

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Data Management

Dylan JonesAugust 10, 2015 0

Justifying the need for a data governance business case

Many people who plan data governance initiatives ignore the need for a business case. "We've already had approval for the project; why do we need a business case when we've got the budget signed off?" The perception is that because they have a strong commitment, there is no need to get

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