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TDWI Articles

Contributor: Mike Shiff


Michael A. Schiff is founder and principal analyst of MAS Strategies, which specializes in formulating effective data warehousing strategies. With more than four decades of industry experience as a developer, user, consultant, vendor, and industry analyst, Mike is an expert in developing, marketing, and implementing solutions that transform operational data into useful decision-enabling information.

His prior experience as an IT director and systems and programming manager provide him with a thorough understanding of the technical, business, and political issues that must be addressed for any successful implementation. With Bachelor and Master of Science degrees from MIT's Sloan School of Management and as a certified financial planner, Mike can address both the technical and financial aspects of data warehousing and business intelligence.


All articles by Mike Schiff


Leverage Your Data for Better Customer Service

Even when organizations have the necessary data to improve service processes, customers may still receive confusing communications that make organizations seem incompetent.

Take Care When Applying Predictive Analytics

Predictive analytics can get things wrong. Here's what your enterprise needs to do to prevent problems or public relations disasters.

How Accurate Are Your Data Sources?

We often assume that data obtained from outside sources meets the same quality standards as data from our own operational systems. Unfortunately, this may not be true.

Cloud Deployments: Benefiting User, Developer, and Vendor Communities

Vendors should consider the cloud as more than another direct revenue channel. Don't overlook the ways you can benefit from offering a cloud-based solution.

Save Your Data? Maybe, Maybe Not!

Rather than saving every piece of data by default, enterprises should evaluate their data and assess whether keeping it is a potential value or a potential risk.

For Data Scientists, Data and Analytics Skills Are Not Enough

Data scientist is a wildly popular job title, but a good data scientist needs more than strong analytics skills. Knowing the business is crucial.

That Was the Year That Was: Major Data Warehousing Events of 2015 (and Predictions for 2016)

How accurate were our data warehousing observer's predictions, and what's ahead for 2016?

That Was the Year That Was: Major Data Warehousing Events of 2015 (and Predictions for 2016)

How accurate were our data warehousing observer's predictions, and what's ahead for 2016?

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