Data Cleansing

Big Data = Big Data quality issues:

  • legacy systems with different business rules, data models, or formats
  • inconsistent application usage
  • sources providing free text/unstructured data

We offer data laundry services through statistical data cleansing also using the very latest in statistical semantic technology to clean structured and unstructured data.

We de-duplicate, merge, rebuild, structure, normalize, enrich and verify your data so it is clean for further use.

Our services will support you in migrating from legacy systems, keeping your ERP, CRM, and MDM data clean, extracting data from unstructured sources, merging with external data, exporting to other platforms, etc...

 

For example: you have an important SAP database that is used every day by everyone in the organization

After many years of productive use and growth the whole database has become one big pile of trouble; duplicates, mix-ups, invalid old numbers, inconsistent naming, etc... How can you ever get out of that situation?

  • Hire a lot of people to check everything manually? Sure, if you have the budget for man-years of work
  • Throw everything away and start a new database from scratch? Your organization can't afford to come to a complete halt in order to do this. And how do you prevent the same errors from popping up again?
  • Contact Twenty54Labs !

We can dramatically improve the quality and usability of your database, at a fraction of the time and budget needed with other solutions. And we show you how to prevent problems from re-appearing in the future.

Assignments typically become a 3 step process, each with its own characteristics:

  1. Validation
  2. Merging
  3. Creation

This sequence allows for a very speedy progression through your project. Contrary to regular semantic technology, our statistical semantic technology does not require exhaustive topic expert input before the project can start. It is also language independent.
Deep into the project (2/3 rd) we usually start to involve topics experts. On top of that, we enrich data with information from other sources in- and outside your organization. In the final stage we run quality checks via sampling with the help of topic experts.

Curious? Have a look at our Data Cleansing whitepaper