data management for analytics

9月 022016
 

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 […]

The post Is data quality a component of data preparation? Or vice versa? appeared first on The Data Roundtable.

8月 292016
 

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 […]

The post Data preparation strengthens Hadoop information chain appeared first on The Data Roundtable.

8月 222016
 

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 […]

The post Clean-up woman: Part 2 appeared first on The Data Roundtable.

8月 172016
 

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 […]

The post Data prep considerations for analytics, Part 1 appeared first on The Data Roundtable.

8月 152016
 

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 […]

The post Data cataloging for data asset crowdsourcing appeared first on The Data Roundtable.

8月 102016
 

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. […]

The post Clean-up woman: Part 1 appeared first on The Data Roundtable.

8月 082016
 

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 […]

The post Data prep and self-service analytics – Turning point for governance and quality efforts? appeared first on The Data Roundtable.

8月 032016
 

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 […]

The post Who was that masked data? appeared first on The Data Roundtable.

8月 022016
 

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 […]

The post Crowdsourcing data assets in the data lake appeared first on The Data Roundtable.