5-SECOND SUMMARY:
- What is Lumada Data Catalog and how to take advantage of this new tool;
- How to catalogue, organise, control sensitive data and manage redundant data, and also, how to manage all the owners and stewards in your data catalogues.
What would you do if you knew that the way you organise data could be greatly improved? The information gathered from the existing inputs to your company gets bigger every day, and in a way, you need to treat that with big data tools and processes. However, as time passes and the data you store gets wider, the risks of having everything unorganised and losing track of what’s happening increase. This may lead you to spend human hours trying to discover what you want to analyse or being out of bounds in terms of sensitive data compliance. In truth, how can you be data-driven if, in fact, you can’t find data?
Information is everywhere, which we then turn into efficient accessible knowledge by organising and categorising by subject. This happens with books, presentations, code, any other type of information, and now, with data. By cataloguing the information you retrieve from your company’s inputs, you can label and easily find the data you want to work on to prevent the risks we spoke about before. One of the tools that give you the power to achieve that is the Lumada Data Catalog. This Hitachi tool lets you catalogue your data using artificial intelligence and machine learning algorithms that give labels to your data and validate those tags with statistical evaluations, which you can then confirm if they’re right or wrong and teach the algorithm how to perform with your data. But what can you really do with this tool and what value can you retrieve from it? Let’s look at the facts:
1. Organize & Discover Data Quickly
Having all your data catalogued is like having an index for it. You can access and discover specific blocks of information by using the tags functionality. How does this happen? The Lumada Data Catalog uses an AI process that populates your data catalogue automatically, reducing the need to manually discover and tag data because, for huge amounts of information, manual discovery is not manageable anymore. After that, you can accept those tags or add new ones, such as the ones you like to use or your business terms, to classify your data and make the AI process do the rest for you. This gives you the ability to have all your data inventoried and you’ll just need to search for the specific tags you want.
2. Control Sensitive Data
While identifying and tagging data, the Data Catalog AI process will automatically get all of the sensitive data it can find and give it the proper label. If there were other data fields you would like to label as sensitive, you would just need to give the same tag to them. This gives instant knowledge and the ability to maintain your company’s compliance with data privacy regulations.
3. Manage Redundant Data
Maybe you don’t notice, but it’s really easy to have redundant data. Normally the way you know that is when you have the same field coming from different places and you don’t know which one to use. Having your data organised and catalogued you can recognise when you have redundant data and where it comes from, which helps you quickly manage this kind of inconvenience.
4. Owners and Stewards
When you have a data catalogue it’s like having a library and as such, you must have someone guarding everything. That’s why you have owners and data stewards. These roles maintain and manage your data catalogue and help your end users every time they have a doubt or need to find something. By having these people you’re giving a contact point to everyone in your company regarding any matter about data.
Final Thoughts
It’s clear that having a data catalogue can really improve the way you treat and share data across your company. Besides that, treating your sensitive data properly and having specialised people managing your data, with whom your end users can talk, and following procedures is the right way of working as a data-driven company. The Lumada Data Catalog can improve this process even further by using AI and machine learning technologies that let you organize everything automatically. This can bring faster insights and decision making to your company and leverage your capability of being competitive in today’s markets.
Data Analytics Engineer