Data Management | Internet of Things

Saurabh MishraSeptember 5, 2016 0

How to manage the IoT analytical lifecycle

Since the idea of an “IoT analytical lifecycle,” may be understood in many different ways, let’s start with a definition. Performing analytics at the data center and the cloud is well established practice, and is still quite relevant. With growing numbers of connected devices and availability of computing capabilities at

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Manufacturing

Data Management

Phil SimonSeptember 2, 2016 0

Data prep should not be a one-time exercise

.@philsimon on the downside of the Band-Aid approach.

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English

Data Management

Jim HarrisSeptember 1, 2016 0

Is data quality a component of data preparation? Or vice versa?

Critical business applications depend on the enterprise creating and maintaining high-quality data. So, whenever new data is received – especially from a new source – it’s great when that source can provide data without defects or other data quality issues. The recent rise in self-service data preparation options has definitely improved the quality of

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Data Management | Internet of Things

Todd WrightAugust 30, 2016 0

Streaming data and wearables: Allies against rising health care costs

It’s nearly impossible to avoid the debate. From politicians and pundit commentary, to dinner table discussions across the United States, the hot topic for the last several years has been the rising cost of health care. Consider that health care expenditures in the US were $3 trillion in 2014 and are

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English

Data Management

Helmut PlinkeAugust 30, 2016 0

Improve matching results with suggestion based matching in SAS Data Quality

Have you ever had problems matching data that has typographical errors in it? Because of the nature of arbitrary typos and incorrect spelled words a specific matching technique is required to tackle those cases. SAS Data Quality, with its traditional, in nature deterministic matching approach is by nature not best

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English

Data Management

Dylan JonesAugust 29, 2016 0

Data preparation strengthens Hadoop information chain

Hadoop has driven an enormous amount of data analytics activity lately. And this poses a problem for many practitioners coming from the traditional relational database management system (RDBMS) world. Hadoop is well known for having lots of variety in the structure of data it stores and processes. But it's fair to

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English

Data Management

Tom DavenportAugust 26, 2016 0

5 steps to analytic modernization

Some organizations I visit don’t seem to have changed their analytics technology environment much since the early days of IT. I often encounter companies with 70s-era base statistical packages running on mainframes or large servers, data warehouses (originated in the 80s), and lots of reporting applications. These tools usually continue

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English

Data Management

Matthew MagneAugust 25, 2016 0

What can a garage storage system, kayak and surfboard teach you about data modernization?

Two years ago, I found myself the proud, first-time owner of a garage. My wife and I quickly started to add new items to the garage – a battery-powered lawn mower, two beach cruisers and four Tommy Bahama beach chairs. They were stored with ease. What a fantastic world I'd been missing out on. But it wasn't long before we outstripped our

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English

Data Management

Phil SimonAugust 24, 2016 0

Data prep considerations for analytics, Part 2

.@philsimon continues his series on data prep and anlytics.

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English

Data Management

Joyce Norris-MontanariAugust 22, 2016 0

Clean-up woman: Part 2

In my last post, I talked about how data still needs to be cleaned up – and data strategy still needs to be re-evaluated – as we start to work with nontraditional databases and other new technologies. There are lots of ways to use these new platforms (like Hadoop). For example, many

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English

Data Management

Phil SimonAugust 17, 2016 0

Data prep considerations for analytics, Part 1

I'm hard-pressed to think of a trendier yet more amorphous term today than analytics. It seems that every organization wants to take advantage of analytics, but few really are doing that – at least to the extent possible. This topic interests me quite a bit, and I hope to explore

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English

Advanced Analytics | Data Management

Charlie ChaseAugust 15, 2016 0

The Demand Signal Management Proposition

"Tap into all your demand signals. Organize. Visualize. Analyze. Predict. Orchestrate. Optimize." The availability and collection of data are compelling companies to invest in demand signal management solutions to take advantage of the vast amount of information to support their planning processes. However, many have not gotten the return on

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English

Manufacturing

Data Management

David LoshinAugust 15, 2016 0

Data cataloging for data asset crowdsourcing

What does it really mean when we talk about the concept of a data asset? For the purposes of this discussion, let's say that a data asset is a manifestation of information that can be monetized. In my last post we explored how bringing many data artifacts together in a

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English

Data Management

Joyce Norris-MontanariAugust 10, 2016 0

Clean-up woman: Part 1

If your enterprise is working with Hadoop, MongoDB or other nontraditional databases, then you need to evaluate your data strategy. A data strategy must adapt to current data trends based on business requirements. So am I still the clean-up woman? The answer is YES! I still work on the quality of the data.

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English

Data Management

Dylan JonesAugust 8, 2016 0

Data prep and self-service analytics – Turning point for governance and quality efforts?

The demand for data preparation solutions is at an all-time high, and it's primarily driven by the demand for self-service analytics. Ten years ago, if you were a business leader that wanted to get more in-depth information on a particular KPI, you would typically issue a reporting request to IT

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English

Data Management

Emanuela SfercoAugust 5, 2016 0

Why does your company need an analytics culture?

The digital disruption is creating unforeseen events, such as new competitors, products and services that threaten the performance and positioning of consolidated players. Big data and analytics prove themselves, through successful user cases, as the answer to intercept the demand, prevent churn, draw an integrated view of the customer, manage

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English

Data Management

Phil SimonAugust 4, 2016 0

Modernization requires unification

.@philsimon channels his inner Queen Latifa.

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English

Data Management

Jim HarrisAugust 3, 2016 0

Who was that masked data?

Data access and data privacy are often fundamentally at odds with each other. Organizations want unfettered access to the data describing customers. Meanwhile, customers want their data – especially their personally identifiable information – to remain as private as possible. Organizations need to protect data privacy by only granting data access to authorized

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English

Data Management | Fraud & Security Intelligence

Henrik KiertznerAugust 3, 2016 0

How will Brexit impact cybersecurity?

Some weeks have passed since the United Kingdom voted, by a margin of 52 per cent for and 48 per cent against, to leave the European Union, the organization it's been a leading member of since 1973. The tumultuous global reaction to the vote has those of us in information

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English

Manufacturing

Data Management

David LoshinAugust 1, 2016 0

Crowdsourcing data assets in the data lake

A long time ago, I worked for a company that had positioned itself as basically a third-party “data trust” to perform collaborative analytics. The business proposition was to engage different types of organizations whose customer bases overlapped, ingest their data sets, and perform a number of analyses using the accumulated

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English

Data Management

Phil SimonJuly 28, 2016 0

ETL and data warehouses are dead! Long live ETL and data warehouses!

Why they will still play a valuable role in organizational data-management and -integration efforts.

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English

Data Management

Joyce Norris-MontanariJuly 27, 2016 0

Hadoop and MDM – Who is the master?

Today, I was in a conversation about using Hadoop (a big data platform) for master data management (MDM). I still find it amazing when we have the discussion of what systems feed another system. Many of our friends have spent years creating MDM for customer, product, etc. with success. I'm a

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English

Data Management

Dylan JonesJuly 26, 2016 0

Modernisation is the new normal

In my last post, I talked about how to observe the impact of modernisation through a data quality lens. I asked you to consider the quality of your legacy data and what that means on the "shiny new toy" you intend to buy in the future. In this post, I

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English

Data Management | Programming Tips

Nicolas RobertJuly 25, 2016 0

Four ways to conduct a web search for business terms with SAS Business Data Network

SAS Business Data Network is SAS’ solution for managing glossaries of common business terms. This is part of the SAS Data Governance offering as well as bundled with Advanced versions of all SAS Data Management bundles. One thing that is important regarding Data Governance in general, and this solution in

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English

Data Management | Programming Tips

Mary Kathryn QueenJuly 21, 2016 0

Using an alternate Quality Knowledge Base (QKB) in a DataFlux Data Management Studio data job

In DataFlux Data Management Studio, the predominate component of the SAS Data Quality bundle, the data quality nodes in a data job use definitions from something called the SAS Quality Knowledge Base (QKB). The QKB supports over 25 languages and provides a set of pre-built rules, definitions and reference data

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English

Data Management

Phil SimonJuly 20, 2016 0

Four DI modernization mistakes

.@philsimon with some recommendations on modernization.

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English

Data Management

Patryk ChorośJuly 19, 2016 0

Data Governance – first steps – part 4 of 4

At this stage, our organization has defined business objectives for Data Governance programme and shares business term definitions which it uses. This logical area of data and information management has been supplemented with a bridge to technical metadata – in the previous step we obtained one place, which combines the

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English

Data Management

Jim HarrisJuly 18, 2016 0

Modernization and data-driven culture – Part 2

Modernization is a term used to describe the necessary evolution of information technologies that organizations rely on to remain competitive in today’s constantly changing business world. New technologies – many designed to better leverage big data – challenge existing data infrastructures and business models. This forces enterprises to modernize their approach to data

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English

Data Management

Chris HartmannJuly 14, 2016 0

Data ops: Better way to prepare data for analytics and IoT?

We all find change easier when it starts with something we’re familiar with. That’s why I think sports analytics examples are popular – most of us are sports fans, so we get it more easily. It’s also why automotive examples that illustrate the potential reach of the Internet of Things

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English

Data Management

David LoshinJuly 13, 2016 0

A modernized approach to data lake management

In my last post, I started to look at the use of Hadoop in general and the data lake concept in particular as part of a plan for modernizing the data environment. There are surely benefits to the data lake, especially when it's deployed using a low-cost, scalable hardware platform.

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English