Ignite your predictive analytics with Spark

Writer and Content Strategist, IBM Information & Analytics Group

Everywhere you go, people are talking about Apache Spark, the fast and flexible open source engine for large-scale data processing. But what is it, and what does it mean for big data analytics? 

Spark is an open source engine built specifically for data science. It helps simplify algorithm development and accelerate analytics results. With Spark, you can better extract value from big data, conducting deeper analyses and delivering results faster, all while reducing the time and effort required for coding. 

There’s a good reason for all this interest. Spark accelerates analytics on Hadoop, delivering unheard-of speed—up to 100 times faster than Hadoop MapReduce in memory—to data scientists and developers working with big data at scale

It enables you to write applications quickly in Java, Scala, Python or R. And Spark also includes a full suite of complementary tools, including a machine-learning library (MLlib), a graph processing engine (GraphX) and stream processing. Highly versatile in many environments, Spark is known for its ease of use in creating algorithms that harness insight from big data. In fact, Spark is being used right now by a range of organizations for innovative, real-world analytics use cases, and the list is growing. example: 

  • A credit reporting firm creates personalized experiences using Spark.
  • A mobile fitness app uses Spark to clean up user-entered food data and build different recommendation systems for recipes and meals.
  • A restaurant reservation website uses Spark for log processing and extract, transfer and load (ETL) and is evaluating Spark Streaming for real-time analytics.
  • A telecommunications firm analyzes its customers’ mobile usage patterns.
  • A location technology company enables brands to reach on-the-go consumers.

If you can harness the power of big data, you can monetize data into valuable insights that can help identify emerging opportunities, improve the customer experience, enhance operational efficiencies, reduce risks and more.

The question remains: Are the benefits of Spark available only to anyone who’s skilled in writing code? Not with IBM SPSS software. IBM SPSS Modeler and IBM SPSS Analytic Server abstract the complexity of the Spark environment and let users interact with a familiar graphical user interface, allowing them to take advantage of the power of Spark without having to write code.

Take your Spark journey to the next step. IBM invites you to a free 3-month trial of IBM Analytics for Apache Spark and IBM Cloudant. Use Spark in the cloud to conduct fast in-memory analytics on your Cloudant JSON data. Sign up today and also receive free SaaS Startup Advisory Services to help you accelerate your time to results.