Leverage your existing data with minimal effort

25 November 2020
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Do most data blogs make you feel like everything you should do is expensive, time consuming and requires complex skills? Well, this blog is different. Here are 5 practical recommendations (in no particular order) to leverage your existing business data with less effort than you think.

Create a Data Catalog

Think of a data catalog as an inventory of your company's data that includes descriptions, locations and other useful information about the usage and context. The same way you keep an inventory of the products and materials stored in your warehouse, you want to offer your employees an overview of the data stored in your databases, data lakes, cloud storage etc.

The goal of a data catalog is to make your data accessible and understandable to whomever needs it within your organization for operational purposes, reporting or analysis. These are some functionalities your data catalog should provide are: 

  • automated metadata collection
  • advanced search capabilities 
  • data evaluation

It's likely that your current technology vendors provide data cataloging features as part of their products, so try to capitalize on what you already have.

Create an ODS layer in your data architecture

Did you ever want to check the results of a new campaign, a change of settings or a newly installed module of one of your operational systems, but you couldn't see the results yet because the development team still had to add them to the reporting environment? We hear you.

This is a situation where an Operational Data Store (ODS) layer might be the perfect solution for you. The ODS stores a copy of your most important operational data and is typically used as a source for your data warehouse, but it can be more than that. Having this layer means you have a copy of the data ready for operational reporting and some quick insights. 

Up your game even more by analyzing the data using a self-service ETL tool, but do not forget to industrialize your insight by passing it on to your developers. Think of the ODS layer as your fast analysis sandbox for data you already have.

Don't forget to visualize your findings

Visualization is a powerful way to communicate the outcome of your analysis. Data visualization might already be a method for discovery and exploration, but it should definitely be the final step towards delivering your findings to the business.

Many visualization tools are equipped to transform, clean and filter data sets on the spot. However, more important than the tool you're using is the design of your visual. A proper report or dashboard design should: 

  • ensure that your readers quickly get a grasp of the main insights
  • have the possibility to explore the reasons behind them
  • provide the confidence to take adequate decisions and actions
  • keep your message clear from clutter
  • and takes your target audience into account at any time

Distribute and publish

Unless you run a one-man business, you probably want to share your data findings. Especially when sharing reports becomes a repeated effort, like a monthly or quarterly sales report, consider to automate the distribution as much as possible. You don't have to rely on exotic tools. On the contrary, try to utilize the communication channels your company is familiar with to limit potential resistance.

Apart from sharing the actual results with the appropriate audience, it might be worthwhile to document and publish your data set, methodology and outcome. Going beyond the departmental borders can have several benefits. These include, but are not limited to data usage, exchange of information, elimination of rework and reduction of data illiteracy. All of these contribute to the establishment of a data culture.

Data quality and data ownership

In today's data-centric business world, losing time and money to data quality issues is something you can't afford and limits the value of your current data. However, dealing with this kind of issues or starting a mission to improve overall data quality isn't always easy.

You cannot address this alone so if you have to start somewhere, start by identifying your data owners. These are the key individuals in your organization that are most knowledgeable about the business data and capable of improving the data quality. Data ownership with defined responsibilities and accountability is indispensable for your path towards implementing data governance and improving data quality.

How can we help?

We’ve helped organizations in various markets implement Data Governance, Business Intelligence, and Data Science projects, working closely with all stakeholders to realize a future-proof data architecture.

Do you struggle to kickstart your data journey or are you uncertain about how to reap the benefits of the data you already have? Don’t hesitate to reach out. We’re here to help.