data management for analytics

9月 102015

I am currently cycling through a schema-on-read data modeling process on a specific task for one of my clients. I have been presented with a data set and have been asked to consider how that data can be best analyzed using a graph-based data management system. My process is to […]

The post Big data model convergence: Combining metadata and data virtualization as a collaboration tool - Part 2 appeared first on The Data Roundtable.

6月 252015

Traditional data governance is all about establishing a boundary around a specific data domain. This translates to establishing authority to define key business terms within that domain; establishing business-driven decision making processes for changing the business terminology and the rules that apply to them; defining content standards (e.g., metadata and […]

The post Big data, big governance appeared first on The Data Roundtable.

5月 202015

(Otherwise known as Truncate – Load – Analyze – Repeat!) After you’ve prepared data for analysis and then analyzed it, how do you complete this process again?  And again? And again? Most analytical applications are created to truncate the prior data, load new data for analysis, analyze it and repeat […]

The post Data management for analysis – Feeding the analytical monster more than once appeared first on The Data Roundtable.

5月 082015

Once you have assessed the types of reporting and analytics projects and activities are to be done by the community of data analysts and consumers and have assessed their business needs and requirements for performance, you can then evaluate – with confidence – how different platforms and tools can be combined to satisfy […]

The post Integration and publication: Data management for analytics appeared first on The Data Roundtable.

5月 062015

In my previous post I used junk drawers as an example of the downside of including more data in our analytics just in case it helps us discover more insights only to end up with more flotsam than findings. In this post I want to float some thoughts about a two-word concept […]

The post Analyzing the data lake appeared first on The Data Roundtable.

5月 042015

In April, the free trial of SAS Data Loader for Hadoop became available globally. Now, you can take a test drive of our new technology designed to increase the speed and ease of managing data within Hadoop. The downloads might take a while (after all, this is big data), but I think you’ll […]

The post Self-service big data preparation in the age of Hadoop appeared first on The Data Roundtable.

4月 292015

In the last post, we talked about creating the requirements for the data analytics, and profiling the data prior to load.  Now, let’s consider how to filter, format and deliver that data to the analytics application. Filter – the act of selecting the data of interest to be used in the […]

The post Filter, format and deliver: Managing data for analytics appeared first on The Data Roundtable.

4月 282015

In the era of big data, we collect, prepare, manage, and analyze a lot of data that is supposed to provide us with a better picture of our customers, partners, products, and services. These vast data murals are impressive to behold, but in painting such a broad canvas, these pictures […]

The post Junk drawers and data analytics appeared first on The Data Roundtable.

4月 272015

One area that often gets overlooked when building out a new data analytics solution is the importance of ensuring accurate and robust data definitions. This is one of those issues that is difficult to detect because unlike a data quality defect, there are no alarms or reports to indicate a […]

The post Accurate data definitions: The keystone to trusted data analytics? appeared first on The Data Roundtable.