Top 8 Data Management Features of BI Tools

Post by 
Reading time: 3 min

(This is a multipart series about how to evaluate and select the right BI tool for you and your team. To see the entire outline of the series and a framework for how to evaluate a BI tool, see How to Select the Best BI Tool for You.)

Like shopping for a car or a new electronic device, there are likely a lot of features that the average Jane won’t need. We aim to cover the breadth of features that the top tools and analysts in the market are talking about.

It’s important to focus on what’s right for you and your use case. We recommend buyers be careful to not let features creep onto their “Want to have” or “Mission critical” lists when doing your research. It can be really easy to learn about a cool feature and then think about all the cool and creative ways you could use it. Curiosity and creativity is to be human.

Remember: You started shopping to fill a specific need. Keep that front and center as you research while getting educated on other cool features and how you may use them after your initial set of requirements are delivered.


Here are the top data management features of BI tools to consider as part of your evaluation.

1. Advanced Data Preparation using Python and R

The solution supports advanced and sophisticated data preparation and pre-processing by using libraries and packages of Python and R programming languages.

2. Data Blending

The solution enables data blending as a feature by combining multiple datasets to create a single, new dataset, which can then be processed or analyzed.

Examples of tools that do this, but not very well, are Tableau where development and maintenance of blending any more than 2 sources is difficult or impossible. On the other hand, the best example we’ve seen in the market come from Looker and similar “schema on read” or “virtualization” tools where you can blend as many sources at scale as you wish to configure.

3. Data Exploration

The solution should be able to explore a large data set which is in an unstructured way to uncover initial patterns, characteristics, and points of interest and describe it using statistical and visualization tools and techniques.

Some teams purchase an additional tool for this sort of analysis, but some tools like Qlik Sense do this out of the box when you connect your data. Some could argue that Looker, by proxy of being in the Google Cloud family, can do this as well but that’s just the Data Prep tool within BiqQuery, which is actually powered by Trifacta.

4. Data Governance

The solution provides features to ensure the analysis and insights are within the governed parameters of the organization’s business procedures, policies, objectives, etc. to mitigate risks of multiple sources of truth and ensure data integrity.

5. Data Modeling

The solution enables creating data models by mapping out, diagramming, and visualizing all the different places that an application stores the information at, and how these sources of data will fit together and flow into one another.

Some teams, including us here at Mashey, often use specific data modeling tools like erwin to accomplish this.

6. Data Preparation

The solution enables data preparation by providing tools for data pre-processing, profiling, cleansing, validation, and transformation for analysis.

7. Metadata Management and Data Catalog

The solution provides a metadata management tool to centralize metadata in one location, give a full view of each piece of data across databases, and contain information about the data's location, profile, statistics, summaries, and comments to help make data sources more discoverable and manageable for users.

8. OLAP and Multi-Dimensional Analysis

The solution enables multi-dimensional analysis by supporting OLAP operations like roll-up, drill-down, slicing, and dicing.

This gives us the shivers because it reminds us of traditional BI tools from 20+ years ago like Cognos, but it is a feather worth mentioning on data handling, nonetheless.


Follow the links above to read more about core functional requirements of a BI and analytics tool.

Did we miss something? Drop us a line and we’ll see about getting it added.

Need help with your BI tool selection? Book a call with us and we’ll see if we can help. If we can point you in the right direction with a short phone call, great! If you’d like to hire us to do an evaluation and selection for you, contact us and we’ll make a selection together.

Join Our
Data Analytics

Expect to hear from us about once a month.
Thank you! Your submission has been received!
Oops! Something went wrong while submitting the form.
THere's More

Post You Might Also Like

All Posts
Change Management

Change Management: Preparing for Change

1 of 3 in our series on preparing your organization for new data analytics capabilities. This post talks about ways to build in adoption from the beginning.
Change Management

Change Management: Managing Change

This is the second post in our series on increasing analytics adoption through change management. This post discusses how to manage change during project implementation.
Change Management

Change Management: Reinforcing Change

This is the third post in our three-part series on increasing user adoption through change management. This post discusses how to maintain new behaviors after project implementation.

5 Factors to Move Your Data and Analytics From Laggard to Leader

The past few years have seen a rapid rise in data analytics throughout industries. Business opportunities and technological innovations continue to raise the bar on the subject, allowing even smaller businesses with limited resources to get into the BI game.

Top 12 Dashboarding and Data Visualization Features of BI Tools

Here are the top dashboarding and data visualization features of BI Tools to consider as part of your evaluation.