Data Analytics

Accelerate to AI, data-driven business with IBM Watson Data Platform

Share this post:

IBM announced a series of upgrades and new offerings to Watson Data Platform, an integrated set of tools, services and data in the IBM Cloud that enables data scientists, developers and business teams to gain intelligence from data.

These new features will provide data professionals with the foundation they need to safely and securely share data across teams and environments, in order to more easily analyze and prepare data for AI applications.

By powering self-service data access and unifying data for visibility across all sources, Watson Data Platform addresses many of the problems data professionals encounter day-to-day, including inaccessible and disparate data sets, and discrete tooling that obstructs collaboration.

These new offerings include:

Data Catalog

• Creates a complete and easily searchable index of all structured and unstructured data living in existing systems, cloud platforms and IoT data streams.

• Provides rules-based governance for controlled data access and a detailed view of who should see and work with different pieces of data to help teams stay within compliance.

• Automatic data profiling and classification, using machine learning to categorize data and assign metatags to quickly organize it into searchable stores.

• Enabled by the open standards base of Watson Data Platform, as well as a wide range of more than 30 connectors to both open and proprietary systems, which brings together a view of all data and organization touches.

Data Refinery

• Eases the complex job of preparing, cleansing and processing data to be shared broadly, as well as for ingestion into AI and machine learning apps.

• Provides quicker discovery, visualization and sharing of data, enabling data scientists to work in real-time with developer and business teams to build new data-based models and functions.

Analytics Engine

• A combined Apache® Spark™ and Apache® Hadoop™ service that acts as an intelligent repository for data, enabling users to understand the size, value and creation of each piece of a large dataset.

• Allows developers and data scientists to collaborate to view and build with the intelligence living in data workloads, without the need to manage the infrastructure intricacies behind it.

• Powered by IBM Cloud Object Storage, the scalable, persistent data storage layer that makes data readily available for processing and analysis. The combination of Cloud Object Storage and Analytics Engine separates compute and storage, enabling companies to take greater advantage of the agility and economics offered by the cloud.

Watson Data Platform in action

How do these new offerings help companies solve complex problems – from increasing customer retention to innovating to bring new products to market? A potential scenario for this new functionality could involve a retail company that wants to explore customer-buying patterns and find new ways to increase sales:

• A data scientist would need to view purchase transactions that live in both on-site servers and cloud databases, shape it into seasonal or demographic-specific categories, and analyze the findings in correlation with customer feedback.

• Tapping into the features of Data Catalog, Data Refinery and Analytics Engine, the data engineer (or data scientist) could access the data where it lives, shape it as needed, and build a machine learning model, all while knowing they’re only working with data they have proper clearance to access (even potentially sensitive information like credit card data).

• This model could then be shared with a developer to quickly deploy it into an AI app that markets season-specific clothing based on customer preferences.

To learn more about IBM Watson Data Platform:

Add Comment
No Comments

Leave a Reply

Your email address will not be published.Required fields are marked *

More Data Analytics Stories

IBM Data Catalog Now Generally Available

We hope you have been having a great experience discovering, cataloguing and governing data with IBM Data Catalog as part of IBM Watson Data Platform. We’d like to inform you that the Data Catalog service is now generally available (GA), and all Beta plan instances will be retired on January 31, 2018.

Continue reading

Convincing the naysayers: proving the business value of streaming analytics technology

There’s a lot of hype around the possibilities of stream computing. It seems like everywhere you look, more and more organizations are touting the benefits of capturing and analyzing large volumes of data at high velocity—and increasing numbers of streaming analytics solutions, both commercial and open source, are flooding the market.

Continue reading

The clock is ticking: catch perishable insights and act on them before time runs out

Change doesn’t stop, so neither should your analytics. You could capture the most crucial, valuable insight of all—but if you don’t identify and act on it while it’s still valid, or before your competitors do, it’s worth nothing. Imagine you’re an electronics company that has sunk thousands of hours and millions of dollars into building a profile of the perfect customer for a new product release. Before you can claw back your investment with a wildly successful launch, a rival comes along and disrupts the entire industry with an innovative device like no one has ever seen before. All that effort and resources expended… all for nothing.

Continue reading