Big data analytics

Big data analytics is the often complex process of examining large and varied data sets, or big data, to uncover information -- such as hidden patterns, unknown correlations, market trends and customer preferences -- that can help organizations make informed business decisions.. See complete definition.

October 29, 2020 29 Oct'20
Voting fraud technology could play role in momentous election

Vendors, academics and data scientists are developing technologies to detect irregularities in voting patterns. The turbulent U.S. election could provide fertile turf for the tools.
October 14, 2020 14 Oct'20
Idera targets cloud data lake market with Qubole acquisition

Qubole joins the Idera Inc. group of software companies, bringing data pipeline capabilities into the group to target customers that need more cloud data storage.
September 22, 2020 22 Sep'20
Ahana releases managed Cloud for Presto service

New Ahana cloud system brings a managed service to market that integrates data management and visualization capabilities to aid in business intelligence and data analytics.
August 19, 2020 19 Aug'20
New Qubole Pipelines Service targets streaming data

Data lake vendor Qubole unveiled a data pipeline service, a new tool designed to enable organizations to manage their increasing amounts of streaming data.

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Big data streaming platforms empower real-time analytics

Data streaming processes are becoming more popular across businesses and industries. Read on to see how streaming platform adoptions are benefiting enterprises. Continue Reading
edge analytics

Edge analytics is an approach to data collection and analysis in which an automated analytical computation is performed on data at a sensor, network switch or other device instead of waiting for the data to be sent back to a centralized data store. Continue Reading
predictive analytics

Predictive analytics is a form of advanced analytics that uses both new and historical data to forecast activity, behavior and trends. Continue Reading

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Event streaming technologies a remedy for big data's onslaught

Event streaming is emerging as a viable method to quickly analyze in real time the torrents of information pouring into collection systems from multiple data sources. Continue Reading
Big data vs. artificial intelligence: How they compare

Artificial intelligence can help synthesize and analyze the large volumes of information provided by big data initiatives. The two are different, but they work well together. Continue Reading
Brain teasers and other fun tips for learning Python

Learn about some interesting ways Python coders can grow their skills in the language and the importance of connecting and learning from others in the community. Continue Reading

Learn to apply best practices and optimize your operations.

8 types of bias in data analysis and how to avoid them

Analytics can exhibit biases that affect the bottom line or incite social outrage through discrimination. It's important to address those biases before problems arise. Continue Reading
Top 5 predictive analytics use cases in enterprises

From marketing to healthcare, looking at past data can be beneficial to forecasting future trends. Read on to understand the most popular use cases for predictive analytics today. Continue Reading
10 types of biases that affect customer data analysis

Analytics can help businesses make data-driven decisions, but common cognitive biases can skew how organizations interpret the information and CX. Continue Reading

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Overcoming the top 3 analytics adoption challenges

Analytics is a growing part of many businesses. Experts talk about some of the most pressing challenges enterprises may face when implementing new analytics strategies. Continue Reading
COVID-19 data resources for volunteering data scientists

Many data scientist are looking to research the novel coronavirus and ways to fight the continued outbreak. Read on for the top COVID-19 data resources for volunteer researchers. Continue Reading
7 steps to a successful data lake implementation

Flooding a Hadoop cluster with data that isn't well organized and managed can stymie analytics efforts. Take these steps to help make your data lake accessible and usable. Continue Reading