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Data Management

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

Analytics | Data Management

SAS ColombiaJanuary 21, 2015 0

Lo que usted debería saber sobre analítica y Hadoop

Esta es la experiencia de Felix Liao, Gerente de Soluciones de Data Management de SAS para Australia y Nueva Zelanda. Nuestro personaje hizo un viaje hace poco por toda Australia visitando algunos clientes para conversar con ellos sobre las tendencias de Analítica y Hadoop. Además de quedar gratamente sorprendido con

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Data Management

Phil SimonJanuary 21, 2015 0

Five data quality archetypes, part 2

@philsimon on the need to recognize DQ differences.

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Data Management

Dylan JonesJanuary 20, 2015 0

Forming data quality habits in 2015

It’s common at the start of a new year to create a long list of resolutions that we hope to achieve. The reality, of course, is by February those resolutions will likely be a distant memory. The key to making any resolution stick is to start small. Create one small

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Data Management

David LoshinJanuary 16, 2015 0

Static Models and Dynamic Data

After working in the data quality industry for a number of years, I have realized that most practitioners tend to have a rather rigid perception of the assertions about the quality of data. Either a data set conforms to the set of data quality criteria and is deemed to be acceptable

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Data Management

Matthew MagneJanuary 15, 2015 0

Big data preparation, big data quality and big data governance, oh my!

This isn't Kansas anymore. Oz has become a sprawling, smart metropolis filled with sensor data. How do we make sense of, clean, govern and glean value from this big data so we can get Dorothy home? The answer is SAS Data Management. With the latest portfolio updates, customers will be

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Data Management

Jim HarrisJanuary 13, 2015 0

Crowdsourcing data improvement: Part 1

James Surowiecki wrote a book about The Wisdom of Crowds. Jeff Howe, who co-coined the term crowdsourcing, wrote a book about Why the Power of the Crowd Is Driving the Future of Business. In this blog series, I explore if it’s wise to crowdsource data improvement, and if the power of the crowd can

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Data Management

Phil SimonJanuary 9, 2015 0

Five data quality archetypes: Part 1

.@philsimon on the different folks you'll encounter in many large organizations.

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Analytics | Data Management

Stuart RoseJanuary 8, 2015 0

What keeps an insurance CEO awake at night?

I cannot speak from experience, but predominately an Insurance CEO has three primary objectives: Grow the business Reduce expenses Ensure compliance. Let’s individually consider each of these objectives in more detail. Grow the Business How does an insurance company grow from a $2bn to a $3bn organization? Essentially, insurance has

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Data Management

Jim HarrisDecember 31, 2014 0

A few New Year’s data resolutions

Since now is the time when we reflect on the past year and make resolutions for next year, in this post I reflect on my Data Roundtable posts from the past year and use them to offer a few New Year’s data resolutions for you and your organization to consider in

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Data Management

Helmut PlinkeDecember 30, 2014 0

Why master data management is more than just data quality

I have participated in many discussions about master data management (MDM) being “just” about improving the quality of master data. Although master data management includes the discipline of data quality, it has a much broader scope. MDM introduces a new approach for managing data that isn't in scope of traditional data quality

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Data Management

Joyce Norris-MontanariDecember 29, 2014 0

Cracking the code to successful conversions: Development, implementation and ongoing support

The last three parts of our conversion blog (see all of the posts here) go hand-in-hand and require the most time on the project plan. Development - During development of the conversion routines, you may want to consider using error handling standards based on corporate standards. This is where data

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Data Management

Phil SimonDecember 24, 2014 0

The Meta Mistake

.@philsimon on the relationship between metadata and unstructured data.

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Data Management

Jim HarrisDecember 24, 2014 0

Data should not be good for goodness sake

As this is the week of Christmas, many, myself included, have Christmas songs stuck in their head. One of these jolly jingles is Santa Claus Is Coming To Town, which includes the line: “He knows if you’ve been bad or good, so be good for goodness sake!” The lyric is a

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Data Management

David LoshinDecember 23, 2014 0

Creating the MDM demo

With our recent client engagements in which the organization is implementing one or more master data management (MDM) projects, I have been advocating that a task to design a demonstration application be added to the early part of the project plan. Many early MDM implementers seem to have taken the

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Data Management

Ivor G. MoanDecember 22, 2014 0

Dead, or as good as dead: The end of an era for thin clients

In an era long gone by (actually not so long ago) we all interacted with computers via terminals to a mainframe or minicomputer systems. Sometimes, you had to book a slot for when you could access and exploit computer resources. The user was subject to interrupted connections or very poor

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Data Management

Joyce Norris-MontanariDecember 22, 2014 0

Cracking the code to successful conversions: Decommission plan

I have a rule – any conversion or upgrade will require the creation of a decommission plan. A decommission plan should include the following: A list and definition of each database, table and column (source and target). A list and definition of each of the current programs in use (you

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Data Management

Joyce Norris-MontanariDecember 19, 2014 0

Cracking the code to successful conversions: Physical data models

The physical data model should represent exactly the way the tables and columns are designed in the in the database management system. I recommend keeping storage, partitioning, indexing and other physical characteristics in the data model if at all possible. This will make upkeep and comparison with the development, test

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Data Management

Dylan JonesDecember 19, 2014 0

Thoughts on dynamic data provenance

We've explored data provenance and the importance of data lineage before on the Data Roundtable (see here). If you are working in a regulated sector such as banking, insurance or healthcare, it is especially important right now and one of the essential elements of data quality that they look for

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Data Management

Phil SimonDecember 18, 2014 0

Can big data and bad administration coexist?

.@philsimon on an important question.

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Data Management

Clemens Knobloch

Clemens KnoblochDecember 17, 2014 0

Next-gen 360° view of customers

For a long time, master data management (MDM) practitioners boasted about their ability to build a 360° view of customers by aggregating and proactively managing information coming from various business applications such as CRM systems, ERP applications, and other operational systems. But was it really a 360° view? What about

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Data Management

Jim HarrisDecember 17, 2014 0

Metadata presents data

‘Tis the season. While the season means different things to different people, its most common theme is people buying things for people. Things that become presents when they are covered in wrapping paper. Two retailers have been running television commercial campaigns this season about how presents are wrapped. One campaign

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Customer Intelligence | Data Management

Kelly McGuireDecember 17, 2014 0

The Analytic Hospitality Executive in 2014: A Review

Well, Analytic Hospitality Executives, the year has once again flown by, and here we sit just before the holidays looking back on 2014, and figuring out what it all means for 2015. I traveled even more than usual this year (if that’s even possible), spending a significant amount of time

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Data Management

Joyce Norris-MontanariDecember 16, 2014 0

Cracking the code to successful conversions: Logical data models

I have a question --- do we need a logical data model for a conversion? Here are my thoughts. I believe the answer is yes if the conversion has any of the following characteristics: The target application is created in-house. This application will more than likely be enhanced in the

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Data Management

David LoshinDecember 16, 2014 0

Master Data Access Use Case #2: The Composite Record

In the last post we looked at the use case for master data in which the consuming application expected a single unique representative record for each unique entity. This would be valuable in situations for batch accesses like SQL queries where aggregates are associated with one and only one entity record.

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Data Management

Clark BradleyDecember 15, 2014 0

The snap, crackle and pop of data management on Hadoop

Data. It's everywhere. It can reside in many places through replication, accessibility needs or infrastructure costs. For reporting, that same data can be structurally changed (denormalized or aggregated) into additional reporting and analytic data repositories. Over time, new sources of enrichment of that data become available through traditional data sources

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Data Management

Cindy EtsellDecember 12, 2014 0

Winning arguments to convince your boss about Hadoop

Getting universal buy in for Hadoop needn’t be an uphill struggle. In many cases, it only takes one pilot project to realize the benefits of low cost storage combined with powerful analytics. The Hadoop topic provoked passionate conversatoin at a recent roundtable discussion attended by over 25 people from a range

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Data Management

Phil SimonDecember 11, 2014 0

When data isn't sticky enough to keep customers

.@philsimon on the stickiness of data

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Data Management

Jim HarrisDecember 10, 2014 0

Data steward is a tough role to play

In my previous post I explained that even if your organization does not have anyone with data steward as their official job title, data stewardship plays a crucial role in data governance and data quality. Let’s assume that this has inspired you to formally make data steward an official job title. How

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Data Management

David LoshinDecember 9, 2014 0

Master data access use case #1: The unique record

Last time I suggested that there are some typical use cases for master data, and this week we will examine the desire for accessibility to a presumed “golden” record that represents “the single source of truth” for a specific entity. I put both of those terms in quotes because I

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Data Management

Joyce Norris-MontanariDecember 8, 2014 0

Cracking the code to successful conversions: Prototype or not!

To perform a successful data conversion, you have to know a number of things. In this series, we have uncovered the following about our conversion: Scope of the conversion Infrastructure for the conversion Source of the conversion Target for the conversion Management for the conversion Testing and Quality Assurance for

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