DATA SWAMPS: ● Data swamps are simply data lakes

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DATA SWAMPS: Data swamps are simply data lakes that are not managed. They are not to be feared. They need to be tamed. Following are four critical steps to avoid a data swamp. 1. Start with Concrete Business Questions 2. Data Quality

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DATA SWAMPS: ● Data swamps are simply data lakes that are not managed.
● They are not to be feared. They need to be tamed.
● Following are four critical steps to avoid a data swamp.
1. Start with Concrete Business Questions
2. Data Quality
3. Audit and Version Management
4. Data Governance<br>
02
1 Start with Concrete Business Questions:
● Simply dumping a horde of data into a data lake, with no tangible purpose in mind, will result in a big business risk.
● The data lake must be enabled to collect the data required to answer your business questions.
● It is suggested to perform a comprehensive analysis of the entire set of data you have and then apply a metadata classification for the data, stating full data lineage for allowing it into the data lake.<br>
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2. Data Quality:
● More data points do not mean that data quality is less relevant.
● Data quality can cause the invalidation of a complete data set, if not dealt with correctly.
3. Audit and Version Management:
● You must always report the following:
• Who used the process?
• When was it used?
• Which version of code was used?<br>