Working with data is hard, especially when you don’t know how much value you can extract from it. If you need fast access to that data, identifying outliers that may indicate systematic problems, or even finding particular analysis cases, this is the time to make a change.
When dealing with a large variety of data, it becomes clear that on some input systems, data is typically not fully structured but still follows specific patterns generating a “data footprint”. If you can easily define this footprint, it can be automatically assessed and identified while the data is being loaded into your Data Mart or Data Lake, ensuring your data is ready to be interpreted by your analytics applications.
Join us for this Webinar and learn how to use Pentaho to assess your data footprint and to avoid spending too much time looking for problems in your input data.
What is Pentaho Data Integration?
Typical painpoints in finding patterns in data and managing the rules to do so
Defining business rules and importing them into the ETL engine
Tagging and statistics
Coping with large varieties of data and complex business rules can be a demanding task. Pentaho Data Integration with its flexibility and tight integration with big data technologies is the right tool for the job, allowing you to get more value from your data.