Best of Upside's Data Digest
Articles examine choosing the correct big data analytics, using geographic data, boosting security with big data, keeping pace with machine learning, using self-service BI, and streaming analytics basics.
- By Quint Turner
- May 6, 2016
Use the Correct Type of Big Data Analytics
(Source: Business 2 Community)
This article argues that the ubiquity of big data as a buzzword has hidden the true point of big data analytics: to 'galvanize' the data and make it actionable. The author outlines five major techniques in data analytics and explains their advantages and disadvantages so you can choose the best one for your next project.
Geographic Data Can Improve Your Analytics
(Source: Information Age)
Few enterprises are tapping in to the power of GIS (geographic information systems) data, which this article calls 'a goldmine.' The author provides advice and real-world examples for how enterprises should properly integrate GIS data with other types of data in order to have the most complete view of their customers.
Boost Security Through Big Data
(Source: Computer Weekly)
According to a recent survey, 53% of enterprises using big data security analytics report 'high' benefits from the practice. After discussing the rest of the survey results, this article explores how big data analytics can improve information security.
Self-Service BI Gaining Popularity
Young workers aren't the only ones interested in self-service tools. According to a recent survey, most enterprise BI leaders agree that self-service data analytics provides significant advantages. This briefing from Forbes explains why and discusses other key findings about self-service BI.
Keep Pace with Data through Machine Learning
(Source: IT Pro Portal)
The amount of data in the world is growing exponentially. Many enterprises have reached information overload due to this flood of data, especially unstructured data. This article explains why machine learning and predictive analytics are the best ways to keep up with the speed of new information.
The Basics of Streaming Analytics
Real-time analytics, or 'streaming analytics,' is the logical evolution of data analytics because enterprises need to process more data more quickly. This article reviews the basics of streaming analytics, offering definitions, pros and cons, and a list of the major players currently in the market.
Quint Turner is an editorial intern at TDWI and an undergraduate English student at Skidmore College. Follow his blog at pungry.com.