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What Happened to Hadoop? And Where Do We Go from Here?

Apache Hadoop emerged on the IT scene in 2006 with the promise to provide organizations with the capability to store an unprecedented volume of data using cheap, commodity hardware. Hadoop facilitated data lakes were accompanied by a number of independent open source compute engines – and on top of that, “open source” meant free! What could go wrong?

How Hadoop Can Help Your Business Manage Big Data

Hadoop. Once largely unknown, hit the scene in part due to the explosion of unstructured data. Download the new white paper, “Making the Most of Your Investment in Hadoop,” through which SQREAM explores an approach to Hadoop that aims to help businesses reduce time-to-insight, increase productivity, empower data teams for better decision making, and increase revenue.

Making the Most of Your Investment in Hadoop

Hadoop came to prominence when the web exploded with unstructured data. The use of unstructured data is common for web analytics, where flexibility is required for unknown or compound fields (arrays, nested objects, or just unknown). Download the new white paper from SQREAM that explores  an approach to Hadoop that aims to help businesses reduce time-to-insight, increase productivity, empower data teams for better decision making, and increase revenue.

The Power of Crunching Big Data Effectively

In this contributed article, Lex Boost, CEO of Leaseweb USA, points out that according to an Accenture study, 79% of enterprise executives agree that companies not embracing big data will lose their competitive edge. Considering that data creation is on track to grow 10-fold by 2025, it’s crucial for companies to be able to process it more quickly, and meaningfully.

Cloudera + Hortonworks: A Marriage from the Edge to AI

Did you hear the clap of thunder in the big data ecosystem today? If so, it was only just Cloudera, Inc. and Hortonworks, Inc. jointly announcing that they have entered into a definitive agreement under which the companies will combine in an all-stock merger of equals. The transaction, which has been unanimously approved by the Boards of Directors of both companies, will create the world’s leading next generation data platform provider.

Hadoop-as-a-Service: The Need Of The Hour For Superior Business Solutions

In this contributed article, content writer Swamini Kulkarni discusses how the launch of new platforms based on HaaS solutions demonstrate that Hadoop-as-a-Service (HaaS) is a promising solution for building and managing the big data cluster, which will compel organizations to consider Hadoop as a potential solution for big data challenges.

Interview: Jamie Engesser, VP Product Mangement at Hortonworks

I recently caught up with Jamie Engesser, VP Product Mangement at Hortonworks during the company’s DataWorks Summit 2018 conference in San Jose, California, to get an update on his company’s direction and his sense for the pulse of the big data industry.

Hortonworks Data Platform 3.0 Enables Containerization and Deep Learning Workloads

Hortonworks, Inc.® (NASDAQ: HDP), a leading provider of global data management solutions, today announced Hortonworks Data Platform (HDP) 3.0, which delivers significant new enterprise features including containerization for faster and easier deployment of applications, and increased developer productivity. The new version of HDP enables customers to more quickly, reliably and securely get value from their data at scale to drive business transformation.

Big Data, Hadoop & Cloud: Tackling a Chain of Emerging Challenges

In this special guest feature, Chandra Ambadipudi, CEO of Clairvoyant, provides a compelling tour de force through the recent history of the big data industry and how Hadoop and the cloud have made steady acceleration possible. Also offered are recommendations for how to address several challenges faced by enterprises with respect to big data cloud implementations.

Business Lessons from Hadoop’s Non-Failure

In this special guest feature, Hiro Yoshikawa, co-founder and CEO of Treasure Data, counters the growing perception that Hadoop is a failure and focuses on the lessons that organizations can learn from the rush to adopt Hadoop.