IBM discloses Hadoop Analytics Tools

IBM has launched its new in-Hadoop analytics to accelerate the conversion of data into insight for the business.

IBM is delivering machine learning and many new features that can run over large scale data in the new IBM BigInsights for Apache Hadoop.

While more companies are using Apache Hadoop for collecting and storing variable data, but are still struggling to realize its full potential in every part of their business.

For example, a business analyst who needs to find relevant information and the data scientists who need to make sense of the data with statistical modeling and the complex environments needs to be easy for IT to manage and deploy for everyone to use.

According to IBM, BigInsights for Apache Hadoop includes a broad data science toolset to query data, visualize, explore and conduct distributed machine learning at scale.

IBM HQ

IBM has introduced three new modules:

IBM BigInsights Analyst: This will include IBM’s SQL engine and spreadsheets as well as visualization to find data. The company says that the number of SQL queries that are running is in the billions and that with BigInsights Analyst, the efficiency can be improved by approximately 2x to 4x on Apache Hadoop.

IBM BigInsights Data Scientist: This will deliver a new machine learning engine that automatically tunes its performance over large scale to find interesting patterns. It will provide a native support for open source R statistical computing so that existing R algorithms can be leveraged.

IBM BigInsights Enterprise Management: This will introduce some new management tools aimed at speeding up the results. These tools will provide multi-tenancy and multi-instance support in a cluster.

IBM also announced the IBM Open Platform with Apache Hadoop which gives the necessary data access controls and authentication for an enterprise.  IBM is also adding support for Apache Spark.

IBM Analytics combines traditional data warehouses technologies with new Big Data techniques, such as Apache Hadoop, stream computing, data exploration, advanced analytics, enterprise integration.

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