data analytics

The Myths of Business Analytics Part 4: Dashboard Tools are Complete Solutions

By |2020-08-04T16:16:55+00:00August 4th, 2020|Data Practices|

In this series we have discussed some of the myths of business analytics, and important components to a successful solution including data lakes and intelligence on your data. Finally, it is time to put the presentation in place. This is where dashboard tools can really shine.    Before embarking on dashboard development it’s important to review your questions and start to sketch out how you

The Myths of Business Analytics Part 3: Intelligence Systems Require a Dedicated Team

By |2020-07-20T18:31:24+00:00July 20th, 2020|Data Practices, Services|

In part 2 of this series we explored the importance of data lakes. With an established data lake, blending that data together in workflows requires analytics tooling. That tooling could include hiring data engineers and data scientists that can code the solution in any number of languages like Python or R. But if you don’t have those kinds of

The Myths of Business Analytics Part 2: Databases Replace Data Lakes

By |2020-06-22T15:43:24+00:00June 22nd, 2020|Data Practices, education|

In part 1 of this series we discussed the confusing landscape of business analytics and the components necessary for a complete solution. In part 2 of the series, we will discuss one aspect of business analytics solutions that is vital for success - the utilization of a data lake. The data lake is a place for all your data sources to enter

Accelerate Your Time to Market

By |2019-04-05T15:05:23+00:00April 4th, 2019|Uncategorized|

From Services Provider to Software Vendor Your service is successful.  You are fulfilling the needs of your customers.  Your reputation is healthy, and now you are looking to expand more.  The most basic expansion strategy is asking what else you can do for your existing customers to strengthen your relationship. Offering a software product is

3 Reasons Faster Achieves More in Analytics

By |2018-04-04T11:40:51+00:00April 4th, 2018|Data Practices|

Interested in a counter-intuitive statistic? In one survey successful business intelligence project leaders reported getting value from their implementations more than twice as fast as those that failed to meet their objectives.  A natural tension usually exists between speed and impact.  When one is prioritized in technology, too often the other suffers.  As indicated in

Observations from AWS re:Invent

By |2017-12-04T17:02:37+00:00December 4th, 2017|Architecture, Artificial Intelligence, Data Practices, Embedded BI, Machine Learning, News|

Amazon certainly knows how to go big at a conference.  With nearly 50,000 attendees AWS re:Invent was spread across Las Vegas hotels and included fully booked sessions from end to end.    Over 1000 sessions were held and venues spanned the MGM, Aria, Venetian, LINQ and Mirage elevating conference logistics and unfortunately wait times to

BI Vendor Analytics – Q4 2017

By |2017-10-19T16:22:36+00:00October 19th, 2017|Uncategorized|

We like to use our data skills to help people. We have found that to be a quick route to trust and credibility. One of our most popular recent posts made use of research Blacklight had conducted on business intelligence tool features. Choosing a BI tool has gotten wildly complicated as the web proliferates with

Avoid Making Your Data Ten Times More Expensive

By |2017-10-16T11:36:30+00:00October 16th, 2017|Data Practices|

When 83% of companies believe their revenue is affected because of data quality problems, we need to take a look at what is going wrong. Few endeavors have received the media attention, promise, and even hype as the revolution organizations today are undergoing to become data-driven. But the value from that investment and work evaporates when the data