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.

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Free Guide: 5 Data Science Tools to Consider

With the right data science tools, you can gain powerful insight out of the ever-growing pools of corporate data. Learn why data science experts are using Python, R, Jupyter Notebook, Tableau, and Keras.

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Big data analytics News

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.
July 14, 2020 14 Jul'20
BigQuery Omni enables Google multi-cloud data analytics

Google BigQuery data analytics users can now query data across clouds from multiple providers, including AWS and Microsoft Azure, without the need to first move the data.
June 12, 2020 12 Jun'20
Data drives the decisions behind making movies

From the moment a script is submitted to the time a movie is released, analytics drive just about every decision made during the making of a feature film.
February 11, 2020 11 Feb'20
Snowflake raises $479 million to boost cloud data warehouse

Snowflake is looking to grow its data warehouse platform with new funding and a partnership with Salesforce that could differentiate its platform from rivals.

Big data analytics Get Started

Bring yourself up to speed with our introductory content

Apache Hadoop YARN

Apache Hadoop YARN is the resource management and job scheduling technology in the open source Hadoop distributed processing framework. Continue Reading
What makes up a strong data science team structure?

Enterprises rely on a strong data science team to get the most from their data. Read on to find out what talents you'll need to employ to support your organization's data. Continue Reading
Data scientist vs. data analyst: Comparing the 2 data roles

The differences can be subtle, but in general, a data scientist has more responsibilities and a more advanced background than analyst counterparts. Continue Reading

Evaluate Big data analytics Vendors & Products

Weigh the pros and cons of technologies, products and projects you are considering.

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
Using data for public good in fight for racial equity

While some data-driven methods recently have been publicly scrutinized for biases in practice, there are plenty of ways data can aid the fight for racial equity. Continue Reading
Metamorphosis of Kafka Confluent event streaming technologies

Kafka Confluent event streaming tools allow data managers, analysts and developers to capture, process, store, access and analyze data streams on the fly with precision. Continue Reading

Manage Big data analytics

Learn to apply best practices and optimize your operations.

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
Find out how smart you are about machine learning and AI

Machine learning can help businesses gain powerful analytics value from their data -- but only if it's done right. How much do you know about machine learning and related forms of AI? Continue Reading
Why organizations need IoT data scientists on their team

IoT is ratcheting up the stakes and creating new ways to use data, making IoT data scientists a necessity for organizations to maintain a competitive edge. Continue Reading

Problem Solve Big data analytics Issues

We’ve gathered up expert advice and tips from professionals like you so that the answers you need are always available.

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