Blogs

Blogs

Data Management

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

Data Management

David LoshinApril 15, 2015 0

Business needs and performance expectations: Data management for analytics

In the last few days, I have heard the term “data lake” bandied about in various client conversations. As with all buzz-term simplifications, the concept of a “data lake” seems appealing, particularly when it is implied to mean “a framework enabling general data accessibility for enterprise information assets.” And of

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Data Management

Jim HarrisApril 10, 2015 0

Hadoop is not Beetlejuice

In the 1988 film Beetlejuice, the title character, hilariously portrayed by Michael Keaton, is a bio exorcist (a ghost capable of scaring the living) hired by a recently deceased couple in an attempt to scare off the new owners of their house. Beetlejuice is summoned by saying his name three times. (Beetlejuice. Beetlejuice. Beetlejuice.) Nowadays

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Data Management | Internet of Things

Suzanne ClaytonApril 9, 2015 0

Will the IoT take us from identity to iDATAty?

The Internet of Things (IoT) is going to take us into the next big technology wave, which will include a massive proliferation of personal connected devices like we have never seen before – cars, toothbrushes, household appliances, watches, medical devices, bicycles, and all sorts of things on our body and in

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Data Management

David LoshinApril 9, 2015 0

Differentiating process, persistence, and publication: Data management for analytics

As part of two of our client engagements, we have been tasked with providing guidance on an analytics environment platform strategy. More concretely, the goal is to assess the systems that currently compose the “data warehouse environment” and determine what the considerations are for determining the optimal platforms to support

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Analytics | Data Management

Dylan JonesApril 8, 2015 0

Lineage, data quality and continuity: Keeping your data analytics healthy

The adoption of data analytics in organisations is widespread these days. Due to the lower costs of ownership and increased ease of deployment, there are realistically no barriers for any organisation wishing to exploit more from their data. This of course presents a challenge because the rate of data analytics adoption

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Analytics | Data Management

Leo SadovyApril 7, 2015 0

Good habits for big data

“Begin with the end in mind” - Habit #2 from Stephen Covey’s ‘Highly Effective People’. The Edge Foundation is based on the premise of: “To arrive at the edge of the world's knowledge, seek out the most complex and sophisticated minds, put them in a room together, and have them

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Data Management

Phil SimonApril 6, 2015 0

The need for speed: A look at real-time analytics

You may feel like the world is moving faster than ever. If so, then you can take solace in two facts: You're not alone in feeling this way. You're right. It is. Celebrating the 25-year anniversary of the Web, The Economist ran a piece examining the increasingly rapid adoption of new technologies.

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Data Management

Alyssa FarrellApril 6, 2015 0

Data streams and data lakes: Utilities adjust to big data vocabulary

As utilities expand analytic capabilities into more areas of the business, the reality of the data management challenge becomes very real. Most have accepted the era of "big data." But what about the quality of that big data? Is it reliable? What about the governance? Have the processes changed since

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Analytics | Data Management | Data Visualization

Alan LipsonApril 3, 2015 0

Four lessons from the Data4Decisions conference

It’s great to get in on something on the ground floor. That’s what happened at the inaugural Data4Decisions Conference and Exhibition held in Raleigh, NC, in March. It brought together business people, academics and students to explore how organizations use data management and analytics technology to enhance business processes and

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Data Management

Stuart RoseApril 2, 2015 0

Data is King

In my last blog I detailed the four primary steps within the analytical lifecycle. The first and most time consuming step is data preparation. Many consider the term “Big Data” overhyped, and certainly overused. But there is no doubt that the explosion of new data is turning the insurance business

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Data Management

Jennifer NenadicApril 1, 2015 0

How to build a data science dream team

As a data scientist, I have the rare privilege of possessing the job title that Tom Davenport and others have dubbed the sexiest job in the 21st Century. As this popular job title catches on, I’ve even noticed a trend where customers make direct requests for help specifically from “the data

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Data Management | Data Visualization

Georgia MarianiMarch 31, 2015 0

How to make your data available, interconnected and usable

It's a common problem: Your organization collects vast amounts and types of data – but it's spread across different departments and locations in various formats and systems. It’s a massive challenge to make all that data available, connected and usable to everyone who needs it. That was the scene at

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Data Management

Joyce Norris-MontanariMarch 31, 2015 0

Hadoop and big data management: How does it fit in the enterprise?

The other day, I was looking at an enterprise architecture diagram, and it actually showed a connection between the marketing database, the Hadoop server and the data warehouse. My response can be summed up in two ways. First, I was amazed! Second, I was very interested on how this customer uses

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Data Management

Sudipta SenMarch 27, 2015 0

Leveraging Analytics for a Successful Online Behavioural Advertising Strategy

In today’s era of digital marketing, advertisers have access to innovative tools and platforms, which enable them to provide Internet users with more personalized ads. Furthermore, in exchange for such helpful and free service, people do not mind sharing a little bit of personal information as it helps them find

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Analytics | Data Management

Ian JonesMarch 27, 2015 0

Oilfield contextual analytics: Do you want to play a game?

In the Cold War techno-thriller WarGames, a marine monitoring a nuclear missile silo deep under the Nevada desert sees a red warning light blink on his console. “Just flick it with your finger,” his colleague tells him. He does, and the bulb goes out. Problem solved. But what will their

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Data Management

Business people discussing who owns big data

Jim HarrisMarch 26, 2015 0

Who owns big data?

Jim Harris says the question of who owns big data is no longer an esoteric concept – it's a frequently debated topic.

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Data Management

Matthew MagneMarch 24, 2015 0

SAS MDM new release brings harmony to big data discord

I've been in many bands over the years- from rock to jazz to orchestra - and each brings with it a different maturity, skill level, attitude, and challenge. Rock is arguably the easiest (and the most fun!) to play, as it involves the least members, lowest skill level, a goodly amount of drama, and the

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Data Management

Matthew MagneMarch 23, 2015 0

EMC and SAS redefine big data analytics with the data lake

Adoption of Hadoop, a low-cost open source platform used for processing and storing massive amounts of data, has exploded by almost 60 percent in the last two years alone according to Gartner. One primary use case for Hadoop is as a data lake – a vast store of raw, minimally processed data. But, in many ways, because

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Data Management

Dylan JonesMarch 19, 2015 0

Stability and predictability: The alternative selling points for your data quality vision?

One thing that always puzzled me when starting out with data quality management was just how difficult it was to obtain management buy-in. I've spoken before on this blog of the times I've witnessed considerable financial losses attributed to poor quality met with a shrug of management shoulders in terms

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Data Management

Phil SimonMarch 17, 2015 0

Finding the signal in the analytics noise

.@philsimon looks under the hood of 'analytics.'

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Data Management

Charlie ChaseMarch 12, 2015 0

Are you using downstream data to improve forecast accuracy?

Downstream data have been electronically available on a weekly basis since the late 1980s. But most companies have been slow to adopt downstream data for planning and forecasting purposes. Let's look at why that is. Downstream data is data that originates downstream on the demand side of the value chain. Examples

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Data Management

Clark BradleyMarch 12, 2015 0

Provisioning data for advanced analytics in Hadoop

The data lake is a great place to take a swim, but is the water clean? My colleague, Matthew Magne, compared big data to the Fire Swamp from The Princess Bride, and it can seem that foreboding. The questions we need to ask are: How was the data transformed and

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Data Management | Internet of Things

David FredeMarch 10, 2015 0

Internet of Things: The industrial internet

Today in manufacturing there has been a lot of investment in automation, supervisory controls, quality, and execution systems. The amount of data produced and now being captured is staggering. The data captured in industry will re-define what is “big” in big data. Yet, for all this investment: Equipment still fails. Scrap

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Data Management

David LoshinMarch 10, 2015 0

Using Hadoop: Emerging options for improved query performance

In my last two posts, we concluded two things. First, because of the need for broadcasting data across the internal network to enable the complete execution of a JOIN query in Hadoop, there is a potential for performance degradation for JOINs on top of files distributed using HDFS. Second, there are

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Data Management

Mazhar LeghariMarch 9, 2015 0

Showing the ugly face of bad data: Part 2

In my previous post, I talked about how a bank realized that data quality was central to some very basic elements of its initiatives, such as know your customer (KYC), customer on-boarding and others. In this blog, let’s explore what this organization did to foster an environment of data quality

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Data Management

Dylan JonesMarch 5, 2015 0

The impact of data quality reach

One of the common traps I see data quality analysts falling into is measuring data quality in a uniform way across the entire data landscape. For example, you may have a transactional dataset that has hundreds of records with missing values or badly entered formats. In contrast, you may have

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Data Management

Matthew MagneMarch 4, 2015 0

SAS Data Loader for Hadoop helps your data heroes navigate the fire swamp of big data

In The Princess Bride, one of my favorite movies, our hero Westley – in an attempt to save his love, Buttercup – has to navigate the Fire Swamp. There, Westley and Buttercup encounter fire spouts, quicksand and the dreaded rodents of unusual size (RUS's). Each time he has a response to the

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Data Management

David LoshinMarch 3, 2015 0

Using Hadoop: Query optimization

In my last post, I pointed out that an uninformed approach to running queries on top of data stored in Hadoop HDFS may lead to unexpected performance degradation for reporting and analysis. The key issue had to do with JOINs in which all the records in one data set needed

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Data Management

Mazhar LeghariMarch 2, 2015 0

Showing the ugly face of bad data: Part 1

Financial institutions are mired with large pools of historic data across multiple line of businesses and systems. However, much of the recent data is being produced externally and is isolated from the decision making and operational banking processes. The limitations of existing banking systems combined with inward-looking and confined data practices

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Data Management

Phil SimonMarch 2, 2015 0

What skills will be required to make sense of big data?

Small data is akin to algebra; big data is like calculus.

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