Managing the Enterprise Data Value Chain

Published on 07 Jun 2021

Whitepaper - Managing the Enterprise Data Value Chain

In 2015 17% of companies were using big data analytics tools, that number has grown to 53% by 2017[1]. Updates in software and technology have made it possible for more organizations to collect, store and analyze their data. Data and analytics empower businesses. They can use this information to predict consumer behavior, make better operational decisions, and calulate the ROI of their marketing efforts, among other things. This white paper by OpenText "Introducing Data Fabric: Analytics Unchained",  provides information on what modern data requirements are and why a data fabric is important. You can learn more about the challenges businesses face with their data and analytics. The white paper presents 2 use cases:

  1. A blue-chip energy organization that is looking for insights on outage detection and prevention
  2. A  B2B retailer that wants a 360° view of the customer

You can see how these organizations used open text solutions to get better insights and learn more about the OpenText information fabric.

See also: The Benefits of Rolling Forecasts Over Annual Planning

What is OpenText?

Opentext is Canada's largest software company. They provide world-leading information management solutions. Their solutions help businesses capture, manage and exchange data and information on a global scale. They offer cloud-native solutions in an integrated and flexible Information Management platform.

Common challenges businesses face with data analytics

Most businesses recognize the importance of data and the insights that can be derived from it. However, there are some common challenges that businesses face when it comes to information management:

Data collection

Data needs to be given to analytics tools in a timely and efficient manner. Otherwise, the insights derived will be less accurate and based on incomplete information. Traditionally, ETL (extract, transform, load) tools are used to transfer data from its source to the analytics tools. Typically this was done overnight. This means that there is a delay between when data is added to the source and when it shows up in the central analytics tool. For example, a sales representative may close a deal and add information about it to the business's CRM at 10.00 AM, this information would not show up in the central Business Insights tool until the next morning. To make data collection and collation more effective businesses need to use modern solutions like API integration or have more frequent data plus. If a business does not process information in real-time, a solution that provides real-time data will not add much value. In such a case, organizations should focus on the freshness of data and adjust data collection according to their requirement.    

Quality of data

Along with collecting data in a timely manner businesses also need to ensure the quality of data being collected. Organizations can improve the quality and efficacy of their analytics teams by reducing the amount of time they need to spend on cleansing and loading data. Information management solutions should automatically validate data and check for basic logic like minimum content, cross-reference checks, validation against dynamic reference data, etc.  

The OpenText Information Fabric can be used to create optimal solutions for the different data analytics requirements businesses may have. It offers a high degree of flexibility to work with an organization's existing data architecture. Download this white paper to learn more. Subscribe to for access to quality resources related to the latest developments in technology.


1. Dec 2017, L. Columbus, "53% Of Companies Are Adopting Big Data Analytics", [available online] available from: [accessed June 2021]


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