Data science for all: it’s a whole new game

Get ready to discover keen data-science insights from noted statistician Nate Silver and other experts, captured in Data Science for All: It’s a Whole New Game, a fascinating IBM web broadcast.

Why analytics for JSON?

As a developer, effective use of data drives your best decisions and empowers your organization through applications. Open source tools like Apache® Spark™ help developers gain quick insights from data in web, mobile and IoT apps, enabling large-scale analysis of JSON without manual data preparation or transformation. Developers can use Spark and Notebook technology to visualize and communicate data analysis findings to broad audiences within their organization.

IBM Cloudant – open for analytics

Your application’s data layer contains invaluable insights about your users. That’s why application data can’t be your organization’s best kept secret — it should be open for exploration and visualization by any team that needs it.

IBM Cloudant, the always-on data layer for web, mobile and IoT apps, is equipped with pre-built connectors to popular analytics tools like Apache Spark and IBM Db2 Warehouse on Cloud, enabling developers and data-science teams to explore JSON data and uncover business insights with ease.

Conduct in-memory analysis of Cloudant JSON data

Analyze Cloudant JSON data in a Python or Scala Notebook application using IBM Analytics for Apache Spark. Spark’s data processing engine runs entirely in memory, so you can load, integrate, transform and analyze massive datasets faster than ever before.

Apply enterprise-scale data science to Cloudant JSON with open source tools

Explore Cloudant JSON with data cleaning and transformation, numerical simulation, statistical modeling, machine learning and more using IBM Watson Studio. Rapidly implement the best open source tools, including Spark and RStudio, to activate insights from your JSON data.

JSON analytics resources for developers

Video: Use Python to load Cloudant data to IBM Analytics for Apache

Learn how to load Cloudant data into IBM Analytics for Apache Spark using a Python notebook.

Tutorial: Using Apache Spark, MLLib, FlightStats and Weather Data

Learn how to build a predictive model that can predict flight delays by using IBM Insights for Weather, Apache Spark and Cloudant.

Webinar: How to Build Analytic Apps with Cloudant

Learn how Cloudant integrates with Spark and Db2 Warehouse on Cloud to create powerful analytic applications used for machine learning, predictive analytics and more.

A complete and effective vision for integrated cloud analytics

Cloudant makes it easy to query data extremely quickly, helping us to develop a clearer picture of our customers in real time, and use those insights to drive smarter decision-making and personalized offers.

Mark Beeson, Manager of Web Services, Skechers

The ability to measure the key factors that drive race performance gives us the ability to set targets for what we want to achieve

Andy Sparks, Director of Track Programs, US Cycling

IBM’s complete vision for integrated cloud analytics is key to the success of our Media Mantra A2SI analytics platform.

Shiv Sehgal, Product Manager, RSG Media

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Application developers

Application developers can find support from IBM’s wide array of fully managed database solutions, whether innovating, designing, coding or testing. Using IBM solutions, you can leverage the most integrated and feature-rich set of development services for data collection and management.

IBM Cloud Data Services labs

The IBM Cloud Data Services developer advocacy team offers free, open source resources to get, build and analyze data in the IBM Cloud.

Get started

Let IBM Cloud guide your journey toward the effective use of analytics and show you how to get maximum leverage from your JSON data.