Data Liabilities

Data Liabilities is not handled properly and can severely damage the value of Data Assets.

If Data Liabilities overcome Data Assets in an organization, it can create negative impact of data value.

In-contrast with Data Assets, if Data hosted in your databases, data warehouse, data marts, data lake, data vault, business vault etc. are not utilized properly with no proper ROI and at the same it can’t be used for revenue generation, nor for management decision making then it becomes a liability for your organization. On other words, you are paying for something and not getting anything.

Data Liabilities can also become the reason for Data Loss and failure to ensure proper handling of data usage, data sharing, data quality and data integrity.

One of the major KPI for any CDO should be to reduce data liabilities as much as possible.

Not to mention, hosting and processing data is not a cheap affair plus if management or users can’t utilize it then it’s not worth storing it.

There can be multiple reasons that assist Data Assets to become Data Liabilities.

• Data Security & Privacy: If due to data security and privacy, relevant users can’t view or utilize data then data is a liability to maintain.
• Data Quality: If users don’t trust data due to bad quality, then data is a liability to maintain.
• Data Democratization: Due to non-data friendly organizational culture, if users are not using data for decision making then data is a liability to maintain.
• Data Self-Service: If business users are unable to play with data by themselves then data is a liability to maintain.
• Master and Reference Data: Due to missing Golden Records by Master data or proper Reference data, it is expected to have redundant data means excess data is a liability to maintain.
• Metadata: Due to missing metadata, if users are spending more time to explore data then ROI vs data becomes less and data becomes liability.
• Data Lineage: If you can’t track data and users are spending more time to find issue resolutions or taking more time to deploy new requirements then ROI vs data become less and data become liability.
• Data Governance: If users are not following standard policies to manage metadata, data architecture, data security and reference data then there are high chances of not meeting high ROI vs data means data become liability.
• Data Catalog: If a business glossary and dictionary is missing, then data governance will become difficult means there are high chances of not meeting high ROI vs data means data become liability.

If any of the above-mentioned is there, means some or the other way there is data underutilization, and any underutilized data is a Liability for an organization.

The two biggest data liabilities are.

• Data Swap
• Dark Data

A tag line for data folks to defend ROI for data governance initiatives 😊.

‘Data Governance keeps balance between Data Asset and Data Liabilities by implementing DLP.’

Note: All above mentioned terminologies are explained separately.