As the role of data grows in importance for organizations, so does the likelihood that you’re storing sensitive data. Whether by internal policy or regulatory mandate, many data types – personal identifiable information, credit card and financial data – must be secured and encrypted.


As data volume grows, driven by an increasing business reliance on analytics and data-driven decision-making, so does the likelihood that sensitive data is part of the overall data aggregation. How can data be seamlessly protected across it’s lifecycle (producing, processing, consuming)?

Whether your data is stored in traditional databases, big data clusters, or monolithic data warehouses, chances are we’ve encrypted it.

There are, however, several challenges associated with big data encryption:

  • There are many ways to encrypt and secure data in databases, such as: encryption at rest, tokenization, column-level encryption, application encryption

  • Data lakes and large data environments are often several solutions all stitched together to achieve the data lifecycle of Producing, Processing, and Consuming. For example, often a Hadoop ingest architecture may feed data into a large data warehouse like Teradata, while reporting is performed by Tableaux.

  • These data environments tend to interconnect many, if not hundreds, of applications that all need access to data. Some require unencrypted data, some are perfectly fine with encrypted data, and some may need partially masked data.

In our experience, consistency is the key. If you can develop a consistent strategy across the environment and lifecycle, then processing systems and applications can access data seamlessly in the way they need to.

Fail to do this, and it’s extremely easy to corrupt data, sometimes in ways that are very difficult to detect.



What is the best strategy to use for encrypting and securing my large data environments? What will the level of effort be, and how long will it take? What kind of disruption to the business will it cause?


  • First, we understand and assess the data environment. Chances are we’ve encrypted it before and will bring a working methodology to your team.

  • We work with you to understand the security requirements, and what the implementation objectives need to be.

  • Our deliverable to you is a report that answers key questions about what an implementation will look like: best and recommended approach, level of effort, resourcing requirements, and disruption assessment. This deliverable is essentially a scope of work you can use to execute the project.


  • Medium / Low

  • Performing a data security assessment is usually a relatively low impact study, the outcome of which gives you a scope of work that can function as a project plan for your security project.


  • Remove the uncertainty and unknowns with a big data encryption effort so you know going in what the dependencies and impact will be.

  • Once you know this, you can confidently undertake an encryption project with high assurance and predictability.