Everyone is talking about data. Companies are treating their data as an asset. People are making money from data, by either generating, selling or processing. So everyone know value or importance of data. But how data is really reliable, how many gives preference to data rather than technology.
As this is a life supported by data, shouldn't we give enough time and priority for data.
Many managers or architects run behind technology to showcase that they have achieved something but not making data like gold - a clean, validated, and accurate.
People do not give enough importance to data management best practices. Data architecture and data governance are very crucial for a successful data organization.
In one of the project I worked recently, the data engineers working their from last many years were not aware about data issues. Many records were duplicate, having incorrect values for important fields, correlated data was incorrectly maintained and so on. And if you run reports on such data they will give wrong results. To avoid such scenarios data management team should focus more on their data rather than technology.
There are few important points to be considered about data management:
In coming articles I will illustrate more on above points with what I learned by my experience!
See you then!
As this is a life supported by data, shouldn't we give enough time and priority for data.
Many managers or architects run behind technology to showcase that they have achieved something but not making data like gold - a clean, validated, and accurate.
People do not give enough importance to data management best practices. Data architecture and data governance are very crucial for a successful data organization.
In one of the project I worked recently, the data engineers working their from last many years were not aware about data issues. Many records were duplicate, having incorrect values for important fields, correlated data was incorrectly maintained and so on. And if you run reports on such data they will give wrong results. To avoid such scenarios data management team should focus more on their data rather than technology.
There are few important points to be considered about data management:
- Data consistency
- Data availability
- Keeping data afresh
- Data security
- Single unified view of heterogeneous data
- And most importantly keep data valuable for business
In coming articles I will illustrate more on above points with what I learned by my experience!
See you then!
