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Top data trends in Banking and Financial Services,
and how Data Observability supports them

There are many challenges ahead for data practitioners and decision-makers having to choose between competing needs and outcomes. But there is one single underlying truth. You need to be able to know what’s going on in terms of the health, lineage, and freshness of your data.

Find out more about the top Data Trends in Data and Analytics for Banking and Finance, and how Data Observability can benefit data teams in this industry.

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About the whitepaper

Discover what are the top 6 Data Trends in Banking and Financial Services, and how Data Observability can help support them with automated tasks such as controlling and alerting on data issues, and identifying redundant data.

In a world where more complex analytics requirements arise, we are seeing the proliferation of data pipelines and requests for access to specific data sets. The data engineering teams are struggling to keep up. The last thing they need to be doing is spending more time than necessary troubleshooting broken pipelines and finding data quality issues.

With this whitepaper, written in collaboration with Agile Lab, you'll get a better understanding of practical ways Data Observability can be a great asset for data professionals in the banking industry, with real-life examples such as how the Kensu Platform is helping UniCredit's data teams.

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