3 business realities fueling the need for enterprise data preparation

Portfolio Product Marketing Manager, DataOps, IBM

Last month, IBM announced the release of Infosphere Advanced Data Preparation, an enterprise data preparation solution that quickly delivers a business-ready data pipeline for all data users. Analysts and leading trade publications took note of the connectivity to existing information architecture, paired with the powerful machine learning-driven data transformation core of the tool. Business Insider, Yahoo! Finance, DBTA and others expressed excitement over the new IBM data solution.

“I think IBM is smart to focus on the development, deployment, monitoring and ongoing management aspects of the modeling lifecycle and developing automation where possible,” said Constellation Research’s VP and principal analyst Doug Henschen. “Why be a ‘me-too’ on prep challenges that [others have already] addressed quite well?” 

InfoSphere Advanced Data Preparation adds to our unique and growing DataOps ecosystem of services and solutions, which already includes governance market-leaders like InfoSphere Information Server and Watson Knowledge Catalog as well as other data pipeline delivery solutions like InfoSphere Virtual Data Pipeline for test data. Our focus on DataOps and information architecture (IA) is critical to help clients on their journey to AI. 

One of the biggest challenges that the DataOps methodology aims to overcome for businesses today is ensuring the right data is available for use by all areas of the business. There can be confusion across IT, data analysts, and business user disciplines. Data users might think, Where is the data I need and where did it come from, what has this data set been used for—and is there better data available for me to use? 

Establishing a data preparation segment in your data strategy is increasingly important to help ease some of the confusion. Enterprise data preparation not only helps accelerate the use of governed data sets for analysis, but also ensures everyone is using the same trusted data across enterprise activities.

The movement IBM has seen recently supporting enterprise data preparation stems from three business goals that have become realities across the entire market.Infosphere advanced data preparation

1.  It’s up to the business user to drive enterprise value

Business users are being asked to thoroughly understand their customers, develop new revenue models, and take products to market at an increased rate. More and more, business users want direct control of data for use in contextualized analysis and activities. Around 70 percent of them feel that their strategic objectives can’t be met without the right data. As expectations rise, so should enterprise support to make the goals achievable.

The typical, iterative process we’ve seen business users employ to get their hands on data is to reach out to IT or a data engineer to find and help them curate data sets. This can be very inefficient for all parties involved. You should be looking to expand your information stack to provide a governed and self-service solution – designed with business users in mind – to sustain a competitive advantage. 

2.  Using automation to help operationalize data

In the age of machine learning and AI, enterprise companies are looking to recover billions of hours of worker productivity. This will come from automating processes like governance policy application, data source connectivity and data transformation. These processes create the foundation necessary to support business-ready data for all data users, whenever they need it. Moreover, it creates support for more advanced AI opportunities. 

Today, only one in 20 companies has extensively incorporated AI in their processes. There is an opportunity to take a step back and ensure enterprise business and data strategies are in alignment to support each other. The more automation your business is able to successfully support, the more use and value can be extracted from data through facilitated experimentation and creating access for business users. 

3.  Prioritizing better integration with enterprise data lakes 

Data lakes are a powerful architectural framework that can set up a business for data maturity when governed and managed. It is typically a strategic journey to successfully build and implement a data lake, so it makes sense that an enterprise would want to put it to use as much as possible. As your information stack continues to grow, it is helpful when new tooling can leverage the rich information assets, metadata and business context available in the data lake.

As enterprises see the value of governing and managing the data lake to support a data pipeline, they will make their existing data lake a key part of their data strategy moving forward. Solutions that take that context in mind will be better-suited to seamlessly integrate and quickly create value for the business.

Setting sights on enterprise data preparation offers an exciting opportunity to get more out of your data by accelerating analysis and action-oriented outcomes.

Learn more about Infosphere Advanced Data Preparation and stay informed on upcoming webinars and announcements.