Data Practices

The Myths of Business Analytics Part 5: Combining the Solution

By |2020-08-25T19:38:39+00:00August 25th, 2020|Artificial Intelligence, Data Practices, Embedded BI, Machine Learning|

The world and the way businesses operate is quickly changing, it is up to each organization to step up to the challenge. The good news is that most organizations have the power to transform their business through data they are likely already collecting. Companies that are waiting for things to “go back to normal” will be left

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

The Myths of Business Analytics Solutions Part 1: The Reframing

By |2020-06-01T16:35:06+00:00May 29th, 2020|Data Practices, education|

While this past decade has shown some remarkable advancements in business analytics tooling, we have also seen tremendous challenges arise in their successful use. Why? Very few organizations have the bandwidth to identify what is needed to complete a business analytics solution, unless they have experts on staff and an informed leadership team ready to

Build and Monetize a Simple Software Product

By |2019-05-25T11:39:51+00:00May 25th, 2019|Data Practices, data science, KNIME, News, Products|

One of the simplest ways to get started with a software product for your customers is to automate the review of data.  That is especially valuable when you can identify events, anomalies or patterns and notify your customers.  This pattern of product is easily monetized because the value proposition is simple.  Use smart machines instead

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

Simple Authentication

By |2017-12-20T14:37:50+00:00December 20th, 2017|Data Practices, Embedded BI, Engineering, Products|

When Blacklight evaluated technologies for the partners in our platform, the cloud provider was a major piece of the decision. We needed a partner that was robust, provides virtually infinite scale, clear pricing and most of all the breadth of tools our customers most need. While other providers offered great integration for a specific stack,

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

Observations from KNIME Summit 2017

By |2017-11-03T17:20:57+00:00November 3rd, 2017|Artificial Intelligence, Data Practices, data science, KNIME, Machine Learning, News|

Any analytics project today requires data integration, cleansing, manipulation and often they require machine learning.  In order to solve these problems a hodge podge of tooling is typically required.  That usually leads to glueing technologies together that were never meant to really work with each other in the same place.   The problem is exacerbated