Data Profiling is the process of analyzing the data that sits in your environment or in a specific system. It allows you to look at data from various perspectives to give you insights that will help manage the data more effectively and efficiently, and allow you to plan better for future IT projects, such as a data migration. Unlike a data quality assessment, a data profiling assessment shows high level information on your system, rather than individual pieces of content. Where a data quality assessment provides qualitative information, a data profiling assessment provides quantitative information.
Benefits of Data Profiling Assessment
- Identify opportunities for reducing project costs
- Better predict project timelines
- Determine likelihood of migration project success
Data Profiling Features
- Obtain accurate sizing of your archive environment
- Validate data extraction tool
- Evaluate data throughput to PST
- Identify inactive (orphan) accounts/data
- Look at stubbed capacity
- Final report outlining analysis and recommendations
Why do organizations need a Data Profiling Assessment?
Oftentimes, we find that archives have become a repository for keeping everything forever. While this might seem like a good approach for data retention, it can increase risk and also costs associated with managing or moving an archive. What a data profiling assessment will do is look at all of the data in your archive and determine how much you actually have. This assessment is used to help create a strategic information management plan. We have found that many clients underestimate the amount of data in their archives, because it’s continually growing. This can lead to inaccurate quotes for budgeting and timelines for a migration project.
How can a Data Assessment identify opportunities for reducing costs?
Many times clients are under the impression that they have to move everything during a data migration; they see it as a forklift of all of their data to a new repository. We encourage our clients to think about whether or not that’s the best approach. Your company may not need to migrate old employees’ emails, and other inactive data. If your archive contains emails that are older than your company’s retention period, these can usually be defensibly deleted rather than migrated to a new repository. Defensibly deleting this data, rather than migrating it to your new archive, can reduce migration costs. Along with saving money, it can lower your legal and compliance risk, and remove clutter. Without knowing what you have, it is difficult to intelligently make these money-saving decisions.
How does a Data Profiling Assessment lead to more accurate timelines?
Our project timelines are based on a number of factors including the amount of archive data, number of servers, and data throughput. It can be difficult for our clients to provide an accurate estimate of the amount of data in their archive. Without evaluating the archive with a Data Assessment, it is difficult to say with certainty how much data is in your archive. While some clients have an accurate estimate of the amount of data, other clients unknowingly provide inaccurate figures, which skews our estimates for both budget and timelines. Many headaches are avoided if we can identify any surprises before the migration gets started. For a little upfront effort, Bishop can make sure we identify all data so that we can provide you with the most accurate timeline. Our Data Profiling Assessment will also provide the data throughput to PST.
The more we know about your archive environment, the more successful and predictable your migration will be. If we’re going in blind, there are bound to be more discoveries and delays along the way. A Data Profiling Assessment will ensure that we get off to a great start and minimize problems before we even begin.
“Bishop’s team kept us on top of what we knew we needed to do and they kept the progress moving forward. Once we were ready to proceed, they all did their part and made it happen quickly and smoothly.” Read More >>
Leif Hansen – Kilpatrick Townsend