Avoid Data-Driven Disaster With Enterprise-Class Data Consistency

Achieving consistency with data is easier said than done, especially today when there are so many data stakeholders involved in every organisation.

You wouldn’t think that something as simple as the “name” and “date” fields within a corporate database could cause so much headache but consider the following scenario.

Let’s say Department A and Department B both obtained information from the same customer but they had slightly different preferences in terms of how the data is recorded. For Department A, the customer in question was stored as “Smith, Anderson”, with a date of birth that read “12/04/1992”.

On the other hand, Department B recorded an “Anderson Smith”, born “04/12/1992”. The question now is: How easily can a central system determine the correct name and birthdate of the customer? Was he (or she) born on December 4th or April 12th?

That’s just one small example of the consistency problem organisations today encounter with data. There’s an infinite number of ways in which data could be stored and that doesn’t include the errors or misspells that can typically be found in databases. For the same customer, “Anderso Smith”, “1/4/1992”, is a valid format, for example, but inaccurate.

Now imagine a company that deals with millions of customers, spread across branches with hundreds of departments and thousands of employees, each with their own “preferred” formats for storing data. It’s almost impossible for the enterprise to have complete visibility over its data if the data is fragmented and inconsistent. Even worse, it can lead to erroneous analysis or predictions.

Ensuring Consistency With a Robust Data Platform
These inconsistencies add up. The more data an organisation collects and accumulates, the more time and effort it will take to cleanse data to ensure that it is consistent throughout the enterprise – time and effort which could be spent on more important tasks such as extracting actionable insights from the data.

Leading data platform Cloudera sees the importance of keeping enterprise-class data consistent in order to avoid such data disasters.

Cloudera Data Platform (CDP) provides a consistent data management platform across on-prem and cloud environments. With their Enterprise Data Hub, you can deliver an integrated suite of analytic engines ranging from stream and batch data processing to data warehousing, operational database and machine learning.

These days, you must depend on automation to ensure the consistency of tremendous amounts of data but the automation has to be reliable and accurate – able to discern between the different data formats, styles of input and flag the company for possible errors.

With Cloudera, you can be guaranteed that your data undergoes a dependable process, from collection, integration, analysis and recovery. You can administer your entire data platform – from edge to AI – with Cloudera Manager, which features automated deployment and configuration, customisable monitoring and reporting, effortless and robust troubleshooting and zero downtime maintenance.

Cloudera’s CDP modernises your IT infrastructure and keeps your data secure – in the cloud or on-premises – while helping you drive new revenue streams, improve customer experience and control costs. Cloudera applies consistent security and governance, enabling users to share and discover data for use across workloads.  All these tools from Cloudera will provide a consistent flow in your data, ensuring that it is secured from mishandling and united for much faster analysis.

As businesses are now becoming more data-driven and collecting more and more data, they have to keep their data consistent across their organisation for better, faster and more analysis.

To ensure the consistency of your enterprise-class data in avoiding data-related disasters, learn more about what Cloudera can do for you here.

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