Building Effective Data Strategies

Tim Tutt

Part 1 of 7 — Data Discovery Strategies

A couple of weeks ago I gave a presentation on the 7 Data Strategies that CDAOs need to make business impact. Over the next 7 blog posts I’m going do a bit of a dive into each of those strategies and what data leaders need to do and be aware of to effectively implement them.

Before we get started, I’ll quickly provide the 7 strategies below:

  1. Data Discovery ← (You are here)
  2. Access Control
  3. Data Lifecycle
  4. Real-Time Processing
  5. Data Analytics & Democratization
  6. Data Storytelling
  7. AI/ML For Data

Alright — let’s dive in…

When building an overarching data strategy for an organization, one of the most critical strategies that needs to be in place is one surrounding data discovery. The core reasoning for this strategy is simple — if no one in your organization knows what data is available or where it is, it will be pretty hard for anyone to get any value from it.

One of the first steps in building and executing an effective data discovery strategy is to establish a data catalog. A data catalog is a centralized inventory of all the data available within an organization. It should provide a detailed description of each data source, including where it comes from, who owns it, and what it contains. A data catalog should also specify the access rules for each data source, such as who can access it and for what purpose.

A data catalog should be regularly updated with information on the frequency of data updates, the last time the data was updated, and any changes to the data schema. Each of these updates should be automated where possible to limit the reliance on human error and the necessity for a data steward to maintain this data. The data schema and definitions of fields should also be documented to ensure that all data is consistently formatted, easy to understand, and usable across the organization.

Gif of a man and a day on the calendar circled to show a reminder to review and update your data discovery strategy regularly to stay ahead.
Review and update your data discovery strategy regularly to stay ahead.

There are several data catalog vendors in the market that offer comprehensive solutions to help organizations establish a strong data discovery strategy. Some of the top vendors include Collibra and Alation. These vendors provide a range of features, including metadata management, data lineage tracking, search and discovery, data profiling, and data governance.

Additionally, many cloud service providers like AWS, Azure, and GCP offer native data catalog services that can integrate with other cloud services, making it easier for organizations to manage their data in the cloud. Each vendor has its own strengths and unique features, so it is important to evaluate them carefully to determine which one best fits your organization’s needs.

Once the data catalog is in place, the next step is to create a robust search function that enables users to easily find the data they need. The search function should allow users to filter data by source, owner, access rules, and type of data. A good search function can save users time and help them quickly find the data they need to make informed decisions.

Hands at a laptop with a two color row of catalog to represent A data catalog, a centralized inventory of all the data available within an organization.
A data catalog is a centralized inventory of all the data available within an organization.

In addition to a data catalog and search function it’s important to establish a data stewardship program. Data stewards are responsible for ensuring that the data within their domain is well-managed and meets the organization’s data standards. Data stewards should be responsible for monitoring data quality, identifying data issues, and ensuring that data is properly classified and labeled.

Finally, it’s important to regularly review and update the data discovery strategy to ensure it continues to meet the organization’s evolving needs. As new data sources are added or data governance policies change, the strategy should be updated accordingly.

With ClearQuery, we enable Data Discovery through our cross-dataset search capability which allows users to uncover where the data they’re interested in exists. Using this capability, even if a user doesn’t have access, they can discover the existence of it and make requests of the owners of that dataset for further investigative analysis as appropriate.

demo to show user uncover where the data they’re interested in exists with ClearQuery cross dataset search
Uncover where the data of interest exists with ease using ClearQuery Cross Dataset Search

In conclusion, an effective data discovery strategy is crucial for organizations to make informed decisions and stay competitive. By establishing a data catalog, search function, governance framework, data stewardship program, and regularly reviewing and updating the strategy, organizations can ensure that their data is easily discoverable and usable across the organization.

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