Data Management

Jim HarrisMarch 23, 2016 0

Self-service data prep versus data quality

Many data quality issues are a result of the distance separating data from the real-world object or entity it attempts to describe. This is the case with master data, which describes parties, products, locations and assets. Customer (one of the roles within party) master data quality issues are rife with examples, especially

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Data Management | Data Visualization

Bill DavisMarch 23, 2016 0

Your Hadoop data visualization questions answered here and at #StrataHadoop

If a picture is worth a thousand words, then visualizing data in Hadoop would be like a billion. Over the last few years, organizations have rushed to leverage the low-cost distributed computing and storage power of Hadoop clusters. As Hadoop environments mature and move away from their initial focus of

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Data Management

Todd WrightMarch 22, 2016 0

SAS Event Stream Processing with Hortonworks – The future is now

Even the most casual observers of the IT space over the last few years are bound to have heard about Hadoop and the advantages it brings. Consider its ability to store data in virtually any format and process it in parallel. Hadoop distributors, such as Hortonworks, can also provide enterprise-level

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Data Management

Phil SimonMarch 21, 2016 0

Five data quality lessons from Amazon

@philsimon on what we can learn about data quality from Jeff Bezos's behemoth.

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Data Management

Bill DavisMarch 18, 2016 0

MapReduce vs. Apache Spark vs. SQL: Your questions answered here and at #StrataHadoop

As the big data era continues to evolve, Hadoop remains the workhorse for distributed computing environments. MapReduce has been the dominant workload in Hadoop, but Spark -- due to its superior in-memory performance -- is seeing rapid acceptance and growing adoption. As the Hadoop ecosystem matures, users need the flexibility to use either traditional MapReduce

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Data Management

David LoshinMarch 16, 2016 0

Big data, data standards and cross-platform integration

At a recent TDWI conference, I was strolling the exhibition floor when I noticed an interesting phenomenon. A surprising percentage of the exhibiting vendors fell into one of two product categories. One group was selling cloud-based or hosted data warehousing and/or analytics services. The other group was selling data integration products. Of

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Data Management | Internet of Things

Bill DavisMarch 15, 2016 0

Your streaming analytics questions answered here and at #StrataHadoop

Streaming analytics is a red hot topic in many industries. As the Internet of Things continues to grow, the ability to process and analyze data from new sources like sensors, mobile phones, and web clickstreams will set you apart from your competition. Event stream processing is a popular way to

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Data Management

Joyce Norris-MontanariMarch 14, 2016 0

Should easy access to data change the data strategy?

In the past, we've always protected our data to create an integrated environment for reporting and analytics. And we tried to protect people from themselves when using and accessing data, which sometimes could have been considered a bottleneck in the process. We instituted guidelines and procedures around: Certification of the data

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Data Management

Dylan JonesMarch 9, 2016 0

Data governance is nothing without data quality

When you spend long enough writing and working in any industry, you inevitably see trends emerge and reach varying levels of maturity. Data governance is one such trend, as you can see from the following Google Trends chart:

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Data Management | Programming Tips

Nicolas RobertMarch 7, 2016 0

Data Governance Series: Share DataFlux Data Quality profiling metrics in SAS Visual Analytics (Part 2)

In this post, I continue the journey of getting data profiling results into SAS Visual Analytics. In my first blog I described the process of collecting DataFlux Data Quality profiling metrics to load a datamart. Now we load this datamart into memory (LASR) and then plug a VA report on

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Data Management

Phil SimonMarch 7, 2016 0

Top 5 data quality mistakes organizations make

.@philsimon lists the gravest data-quality errors.

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Data Management

David LoshinMarch 3, 2016 0

Big data quality with continuations

I've been doing some investigation into Apache Spark, and I'm particularly intrigued by the concept of the resilient distributed dataset, or RDD. According to the Apache Spark website, an RDD is “a fault-tolerant collection of elements that can be operated on in parallel.” Two aspects of the RDD are particularly

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Analytics | Data Management

Sandra HernandezMarch 2, 2016 0

¿Cómo gestionar sus datos para alcanzar sus objetivos de negocio?

¿Cómo las empresas pueden gestionar adecuadamente su gran volumen de información? ¿Están los datos de su organización listos para convertirse en la clave para alcanzar sus objetivos empresariales? ¿Cómo tomar las mejores decisiones a partir de la analítica? No cabe duda, en un mundo cada vez más conectado el Big

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Data Management

Jim HarrisFebruary 29, 2016 0

How big of a deal is big data quality?

Data quality has always been relative and variable, meaning data quality is relative to a particular business use and can vary by user. Data of sufficient quality for one business use may be insufficient for other business uses, and data considered good by one user may be considered bad by others.

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Data Management

Dylan JonesFebruary 23, 2016 0

Scaling a vision for data quality

I recently presented a webinar (via the IAIDQ) on the topic of 7 Habits of Effective Data Quality Leaders. To prepare, I looked back at the many interviews of leading data quality practitioners I had undertaken over the years. A common trait among all these interviews stood out – they

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Data Management

Alan CudneyFebruary 19, 2016 0

Here comes MACRA: Analytics can help you measure and manage

Medicare payment changes are coming. The Centers for Medicare and Medicaid Services (CMS) has announced the intention of increasing the proportion of payments to providers based on outcomes and changes in health status, as opposed to delivery of services. At the January 11th, 2016 J.P. Morgan Annual Health Care Conference,

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Data Management

Michael HerrmannFebruary 19, 2016 0

Banken-Daten-Management: Mehr Schein als Sein?

Aktuell sprechen wir mit vielen Banken über das Management ihrer Daten. Historisch schien die Bereitstellung von Information hinlänglich gelöst: Die IT-Abteilungen stellten diverse Mart-Daten & Analyse-Tools bereit. Punkt. Banken-Daten-Management: Mehr Schein als Sein?

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German

Data Management

Phil SimonFebruary 18, 2016 0

Who's in charge of data quality?

.@philsimon chimes in on this pivotal question.

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Data Management

Joyce Norris-MontanariFebruary 17, 2016 0

Risks to consider when developing a data strategy – Part 2

As I explained in Part 1 of this series, creating a strategy for the data in an organization is not a straightforward task. Two of the most important issues you'll want to address in your data strategy are data quality and big data. Data quality There can be no data that is

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Data Management | Programming Tips

Mary Kathryn QueenFebruary 17, 2016 0

DataFlux Data Management Server 2.7: REST APIs

REpresentational State Transfer (REST) is an architectural style for designing web services that access a system's resources using HTTP methods. With the release of DataFlux Data Management 2.7 earlier this year, three new REST Application Programming Interfaces (APIs) are now available: Data Management Server Batch Jobs Data Management Server Real-time

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Data Management

Carlos LaraFebruary 12, 2016 0

Finding the balance between short- and long-term big data storage

Back before storage became so affordable, cost was the primary factor in determining what data an IT department would store. As George Dyson (author and historian of technology) says, “Big data is what happened when the cost of storing information became less than the cost of making the decision to

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Data Management

Stuart RoseFebruary 12, 2016 0

Big data – game changer for insurers.

A recent survey by Capgemini found that 78% of insurance executive interviewed cited big data analytics as the disruptive force that will have the biggest impact on the insurance industry. That’s the good news. The bad news is that unfortunately traditional data management strategies do not scale to effectively govern

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Data Management | Programming Tips

Nicolas RobertFebruary 11, 2016 0

Data Governance Series: Share DataFlux Data Quality profiling metrics in SAS Visual Analytics

This is my first blog post, and the first of a long series around Data Governance. The first thing I want to discuss is the ability to Share DataFlux Data Quality profiling metrics in SAS Visual Analytics. This post will illustrate how to extract profiling data from the DataFlux repository

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Data Management

Joyce Norris-MontanariFebruary 11, 2016 0

Risks to consider when developing a data strategy – Part 1

Creating a strategy for the data in an organization is not a straightforward task. Not only does our business change – our software solutions also change before we can ever get done with a data strategy. So, I choose to understand that a strategy has a vision, and my vision may change

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Customer Intelligence | Data Management | Fraud & Security Intelligence

Suzanne ClaytonFebruary 11, 2016 0

What's next in digital and mobile?

Last year at Mobile World Congress (MWC), we saw the reality of the IoT come to fruition. We saw leaders like AT&T showing their prototypes of connected cars, containers, agricultural sites, homes, etc. And it's got me wondering what we'll see at the 2016 MWC. In 2015, communications and media

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Data Management

Jim HarrisFebruary 10, 2016 0

How often (and why) does your data strategy need to be updated?

In my previous post, I discussed the characteristics of a strong data strategy, the first of which was that a formal, well-defined strategy exists within your organization. This post discusses how often (and why) your organization’s data strategy needs to be updated. While strategy encompasses and sets the overall direction for

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Data Management

David LoshinFebruary 9, 2016 0

Proposing a business-oriented data strategy

In my two prior posts, I discussed the process of developing a business justification for a data strategy and for assessing an organization's level of maturity with key data management processes and operational procedures. The business justification phase can be used to speculate about the future state of data management required

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Data Management

Leo SadovyFebruary 9, 2016 0

Houston, We have a solution: Data Virtualization

Like most boys my age at that time, I wanted to be an astronaut. Fate, however, intervened, in the form of nearsightedness, so I had to find an alternative occupation.  Coming to my rescue for the launch of Apollo 11 was my father, who presented me with a huge booklet that broke

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Data Management

Matthew MagneFebruary 8, 2016 0

Simplify, secure and speed data access with data virtualization

Data virtualization simplifies increasingly complex data architectures Every few months, another vendor claims one environment will replace all others. We know better. What usually happens is an elongated state of coexistence between traditional technology and the newer, sometimes disruptive one. Eventually, one technology sinks into obsolescence, but it usually takes much longer than we expect. Think of

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Data Management

Lisa DodsonFebruary 5, 2016 0

About Love

Love includes a range of strong and positive emotional and mental states, from the highest virtue to the simplest pleasure. An example of such a wide range of meanings is the fact that the love of a mother is different from the love of a spouse, which, in turn, is

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