What are Data Assets?
Data assets refer to a system, application output file, document, database, or web page that companies use to generate revenues. Data assets are some of the most valuable assets in the technology era, and organizations spend billions of dollars to manage the assets.
Maintaining the company’s data assets help companies improve the way they make decisions, serve customers, and generate new revenue streams. Most technology companies like Facebook, Google, and Netflix mainly rely on their data assets to engineer new products, improve current products, and create better ways of providing value to their customers.
Organizations collect and store data on various events, information, and transactions. Typically, most organizations store data on their customers’ interests, spending behavior, social media, budgets, strategic plans, etc. The collected information is then managed and refined into usable information that allows the organization to serve their clients better and remain competitive among market participants.
How to manage data assets
The following are some of the ways that organizations can manage their data assets effectively:
#1. Reduce the cost of data
Many organizations tend to store a lot of data that remains unused most of the time, resulting in higher data management costs. It also costs higher to store, protect and archive all this data that remains idle in the company. An organization should take steps to reduce data management costs by deleting data that the company no longer needs.
Also, when acquiring new sets of data, the company should only invest in data that they do not have, or if they have to acquire a new set of data that they already have, they should destroy the old data. This would help reduce cases of duplicate data which in return increases data storage costs.
#2. Derive more value from existing data
Another way that a company can manage its data assets is to find new ways of deriving value from the data they already have. For example, the company should re-evaluate the value that it derives from existing data, and determine if there other ways that the company can use to derive more value from the data. Also, it may refine the data to remove any confidential information about the company, and sell the data to third parties and earn extra revenues.
An example of a company that earns revenues through its data is Ohio, USA-based grocery chain Kroger. The company sells in product sales data to packaged goods manufacturers and receives approximately $100 million annually in revenues from this revenue stream.
#3. Data inventory and security
Proper data storage and security are crucial to ensuring the integrity of data. The company should maintain a catalog of all the data they that they own, alongside with a brief description of the data. The description should indicate where the data is stored, when it was created and how it is used.
Also, the data should be easily accessible for the company’s employees, and if they require authorizations to access the data, there should be a clear process of seeking approval. The company should also safeguard the integrity of the data by limiting access to a select number of employees, unless with special permission from a senior executive.
What is a data warehouse?
A data warehouse refers to the system that stores large amounts of valuable information that is used by the company. It considered an essential component of business intelligence, and it receives various forms of data from one or multiple sources. A data warehouse stores both current and historical data in one place, which makes it easy to access the data and generate analytical reports that are used in decision making.
Several steps are followed when creating a data warehouse. The first step involves extracting large volumes of data from various sources and bringing them into a single collection point. The extracted data then goes through cleansing to check and correct any errors to ensure that the data stored is of high quality. The data is then converted to a warehouse format for easy storage and access.
The compiled data then goes through sorting, summarizing and cataloging so that it is easier to use. As the company obtains more data assets, it updates the warehouse data to make it better and accurate. The data is made available for use by professionals for reporting, market research, and decision making.
Determining the return on data assets
The return on data assets measures the ability of an organization to generate revenues from its data inventory. Every year, companies spend billions of dollars on software, computer systems, process automation and data management, and the return on data assets measures how efficiently the organization has succeeded in profiting from its inventory data.
The return is measured by evaluating revenue lines, cost reduction mechanisms, or closed down poorly performing divisions. Companies determine the profits attributable to data assets by creating visual representations that show key performance indicators, trends and revenue streams that can be leveraged.
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