ALERT

[WEBINAR] The Future of Data and Analytics

Hadoop



It can be difficult to combine data from varying sources, but when some of that data is from external sources, that further complicates...

Hadoop Analytics: Even Harder With External Sources


Data from varying sources often must be used in Hadoop, but properly combining those data sources is critical for accurate analytics. One...

Hadoop Analytics: Not So Easy Across Multiple Data Sources


Hadoop is an excellent tool for data analytics, but data must often be collected from varying sources. Using source-agnostic tools can...

Hadoop Analytics: Combining Data Requires a Source-Agnostic Approach


HDFS and HBase are commonly used to manage storage with Hadoop, but now Kudu is working alongside them with better results.

Kudu: A Game Changer in the Hadoop Ecosystem?


Most people associate Hadoop with processing big data, but operational Hadoop opens up numerous other possibilities for enterprise use.

Operational Hadoop in Next-Generation Data Architecture


Data theft is an ever-growing problem, but the combination of big data and Hadoop promises to help identify it before it can do any harm.

Discovering Data Theft Using Hadoop and Big Data


Genome sequencing promises almost limitless possibilities in the field of health research, but it's useless if you can't properly collect,...

Why Hadoop Is a Perfect Match for Genome Sequencing


Fraud is the leading cause of financial loss in the banking industry. However, the combination of Hadoop with machine learning has the...

Machine Learning & Hadoop in Next-Generation Fraud Detection


When it comes to processing big data, Apache Flink has the ability to process static as well as streaming data, making it a useful...

The Importance of Apache Flink in Processing Streaming Data


Big data is streaming into businesses at unprecedented rates, and properly harnessing that data can lead businesses in exciting new...

What Core Business Functions Can Benefit From Hadoop?


Rapid application development is key to efficiency. Apache Spark is helping developers test their ideas even more quickly and easily than...

How Apache Spark Helps Rapid Application Development


Just how difficult is it for a business to adopt Hadoop for big data analysis? Some businesses consider it too difficult and expensive, but...

Is Hadoop Adoption Really Worth It?


The Open Data Platform has the potential to change the way that big data is processed, but many do not understand it or how it can work...

What Is the Open Data Platform and What Is its Relation to Hadoop?


SQL and Hadoop are both powerful tools in their own rights, and together, in SQL on Hadoop, their ability to handle big data analysis is...

How Can SQL on Hadoop Help with Big Data Analysis?


Apache Hadoop is the best-known and most widely used tool for big data analytics. How does its open-source status affect it?

What is the Influence of Open Source on the Apache Hadoop Ecosystem?


While Hadoop has been invaluable for handling big data, its first implementation does have some limitations. However, YARN tackles these...

What are the Advantages of the Hadoop 2.0 (YARN) Framework?


Hadoop is a great way to get the most out of big data, but there are numerous other tools that can work with Hadoop to provide even more...

5 Insights About Big Data (Hadoop) as a Service


In order to really understand big data, you need to understand a bit about Hadoop. Here we'll take a look at the top terms you'll hear in...

The 10 Most Important Hadoop Terms You Need to Know and Understand


In TechWise's first episode, Hadoop is discussed with experts from the Bloor Group, GridGain, Actian, Zettaset and DataTorrent, hosted by...