Category: Data Analytics

IBM launches new Integrated Analytics System with Machine Learning

IBM launches new Integrated Analytics System with Machine Learning

Information analytics has never been a “one size fits all” proposition. That applies to the hardware and software technologies organizations employ, the information being parsed and the goals of specific projects. So it’s worth examining how individual vendors approach analytics and the way they evolve their solutions and services to reflect changes in commercial markets. … Continue reading IBM launches new Integrated Analytics System with Machine Learning

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Analyze clickstream data with IBM Db2 EventStore for customer insights

Analyze clickstream data with IBM Db2 EventStore for customer insights

In this blog, we will look at analyzing the Clickstream data with IBM Db2 EventStore to derive timely insights on interests of retail customers. Typically, ingesting streaming event data, persisting with low latency and analyzing it along with historical event data requires integrating multiple analytic systems. IBM Db2 EventStore is purpose built to simplify the … Continue reading Analyze clickstream data with IBM Db2 EventStore for customer insights

Taking the hard work out of Apache Hadoop

Taking the hard work out of Apache Hadoop

Why did IBM decide to create its own Hadoop and Spark distribution, and why does it need a reference architecture? The ability to collect, manage and analyze big data is one of the key tenets of the IBM cognitive business strategy, as well as being central to the Internet of Things. We see a lot … Continue reading Taking the hard work out of Apache Hadoop

Propelling the future of big data and data science

Propelling the future of big data and data science

Data is a potent business resource and the key to gaining and maintaining competitive advantage. Last month, IBM and Hortonworks announced a partnership to bring data science to the world on an open platform, offering Hortonworks Data Platform (HDP) along with IBM Data Science Experience (DSX) and IBM Big SQL to help everyone from data … Continue reading Propelling the future of big data and data science

Why big data?

Everywhere you go today, people are looking down at a mobile device. They are online, browsing, collaborating, shopping for goods and services and transacting business. And not just consumers are using them. Mobile devices are also being used extensively in business-to-business transactions. Customers and prospects have become empowered in the online world. Social networks and … Continue reading Why big data?

The 3 Cs of big data

We’re all familiar with big data’s varying number of Vs: volume, variety, velocity and veracity. However, taking into consideration the purpose for which insight can be derived from big data is highly important and likely more useful for engineering information systems. This purpose is often characterized by using data to inform enhanced decision making, and … Continue reading The 3 Cs of big data

What is big data? More than volume, velocity and variety…

What is big data? More than volume, velocity and variety…

The Problem(s) Any technology is only useful if it solves a problem (or problems). So what problem(s) does Big Data solve? As we all know, there is data, lots of it: historical data, sure, but also new data generated from social media apps, click stream data from web applications, IoT sensor data, and on and … Continue reading What is big data? More than volume, velocity and variety…