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Best of Upside’s Data Digest

Articles explore data analytics, algorithm bias, big data in small enterprises, creating a data-driven culture, and open source myths.

• By Quint Turner
• September 8, 2016

Put the Enterprise First, Data Second (Source: IT Pro Portal)
Data analytics has become so popular that some enterprises are just obtaining data without a plan of what to use it for, according to this article. The author provides solutions to many common challenges to implementing an actionable analytics program.

Examining Bias in Algorithms Versus Humans (Source: The Conversation)
As long as humans program algorithms, there will be some bias present in the results. However, as this article explains, algorithms can also be used to spot bias and make large-scale improvements.

Big Data in Small Enterprises (Source: Tech.Co)
No matter the size of your enterprise, you can use the insights that are characteristic of big data. This article explains how even smaller enterprises can make better use of their data.

Shifting to a Data-Driven Culture (Source: Business 2 Community)
Re-aligning your enterprise to become data-driven takes more than a data strategy or a data scientist. It takes an entire shift in culture, as explained here.

Creating Long-Term Consumers Through Big Data (Source: Harvard Business Review)
Marketing analytics allows for lots of short-term targeting, but this article claims that big data can also be used to create direct value for consumers, thereby creating long-term customers.

Busting Myths of Open Source (Source: Light Reading)
Open source has come a long way since being described as a "cancer," but suspicion still exists. This article busts the major misconceptions some have about open source.

Drive Data's Value with Curation (Source: Techrepublic)
Because not all data will be useful for your enterprise, selecting what data to use and maintain can bolster your analytics. This article explains how to start effectively curating your enterprise's data.

Profiling Skeptics and Believers in Big Data (Source: icrunchdata.com)
This article explains the prevailing moods around big data and advanced analytics by contrasting an exaggerated profile of those more likely to be skeptical with those likely to be enthusiasts.