Best of TDWI’s Data Digest
Interesting articles we found on the Web focus on a paradigm shift towards Big Data, putting data science in the cloud, unifying customer views, and using semantics and smart data lakes to analyze big data.
Using Semantics and Smart Data Lakes to Analyze Big Data
Big data is, with all the tools available to collect data, often unwieldly large. Pushing all the data into a warehouse or a data lake won’t cut it for extracting value. As this article reveals, smart data lakes can turn large amounts of data into insight in real time if you put effort into it. Furthermore, a smart data lake can split the load and democratize analytics processes.
A Necessary Paradigm Shift towards Big Data
Big data has changed rapidly since the hype cycle started, yet many enterprises are not aware of that and are holding on to outdated views of data. This article advises a shift in how enterprises look at data for the modern business landscape.
Keep Your Data Clean for Best Analytics
(Source: Tech Republic)
Data analysis is simple: garbage in, garbage out. Making sure the data you collected is not garbage? Well, that is more complicated. This article offers five of the best practices to make sure the data you have is not worthless trash.
Putting Data Science in the Cloud for Best Results
(Source: Analytics Vidhya)
Building a good data science platform without using analytics can seem difficult, especially with the growing amounts of data to capture. However, as the price of data storage gets cheaper and computing power gets stronger, data science can be easily done on a cloud. This article takes you through some of the best cloud products as well as the reasons to run data science in the cloud.
Unify all Customer Views with Analytics for Best Customer Experience
(Source: I Crunch Data News)
Customers leave many different traces of data to be collected in a large number of separate databases. However, as the amount of data generated ticks up, unifying all these distinct databases into one view of the customer is the best way to provide the finest customer service possible. This article shows the first step towards making it possible.
The Modernization of BI and Data Analytics
The rapid adoption of big data happening in all enterprises has led to a strategic inflection point that stresses getting the most insight quickly and from all sources. Making sure your enterprise will be able to do that requires modernizing your BI and data analytics. This article calls for a revolution in those two fields in order to keep up and get ahead of the competition.
Quint Turner is an editorial intern at TDWI and an undergraduate English student at Skidmore College. Follow his blog at pungry.com.