Treating Data As An Enterprise Asset In Industry 4.0

Tons of data are generated every day and the enterprises are focusing to identify what information should be considered for value. The enormous reliance on data for achieving enterprise objectives is a challenge in terms of achieving value and managing data. Data may include in the form of documents, catalogs, transactions domains, metrics, etc. It is vital to understand what type of data is important for your business and prioritize it accordingly. Some of the data experts opine treating data just like any other asset and the idea is to provide a roadmap for the centralized data. For example, an ideal e-commerce company generates lots of data regarding the number of people who have

  • Visited their website
  • The age group of the visitors
  • Geographical location
  • New customer or existing customer
  • Number of conversions
  • Customers approach through online advertising or direct visit

Unlock and harness the full potential of your data.

Recent technology innovations have enabled us to capitalize on the opportunities by using the data and also focusing on the customer experience. Data is an important aspect of any product or service and treated as one of the strategic assets for any enterprise. The investment in your data and its related data technologies have a profound impact on your enterprise as it helps to generate revenue streams. Though the methods that are used to evaluate data are complicated to execute, understanding the different characteristics of data enables us to bring out the best from the data.

Data is the new gold

The data passed through various stages of transformation right from raw data to analysis, insights, and value is always an asset. Data collected, managed, deployed, and used in the enterprise is growing in importance and the data can be managed only when it can be measured.

We can achieve the valuation of the data to treat it as an enterprise asset by following these questions.

  • How complete, correct, and exclusive is the data?
  • How relevant is the data that can be used for specific purposes?
  • How much impact did this data have on key business drivers?

How data can be treated to an organization’s unique purposes?

Investing in Data Quality – Enterprises should be focusing on the quality of their data by identifying and fixing data issues such as missing customer records, wrong customer addresses, duplication data, etc that can be responded to with Data stewards and perform any corrective actions accordingly. For example, focusing to get the complete information of the customers at one glance will help to make data-driven decisions.

Data Sharing – Data that is being collected at one point and shared with others should be validated, tracked, and should serve the intended purpose. Data that is ready to be shared should be sourced from the system of record and if the data is sourced from other applications which are not from the source, data results in issues. For example, sharing the number of visitors who visited your website and who couldn’t buy anything to connect them again by email, SMS, etc.

Monitoring your Data – Monitor your data so you can keep track of how it changes over a period of time. By monitoring your data you can identify the sources of the problems that can be well identified and also helps in understanding business insights. If you are focusing On your MDM customer information, you can observe the customer’s data changes and help you to focus on the latest trends in your data. For example, focusing on both existing and new customers regarding their buying preferences so that you can generate ads that would focus on their interests.

Planning and Data Governance – At the enterprise level, Data governance or Data Governance solutions are one of the key factors for any successful data asset management. Data Governance is related to the process that controls the creation, sharing, using, and accessing of information. For example, you can make sound decisions based on empirical data which helps to create a win-to-win situation.

Data Governance helps to

  • To develop a strategy
  • Identify master data
  • Decide what data to manage
  • Define data quality, integrity, classifications, security, and use of data
  • Metadata and documentation requirements.
  • Address business rule issues, quality issues, and security issues

To explore more, you can request a demo regarding Amurta’s Data Insights Platform by just filling out an inquiry form. To know more information and for any queries please feel free to contact us at +1 888 840 0098 and you can email us at, we will be happy to assist you.

Treating Data As An Enterprise Asset In Industry 4.0

Data is the new gold