Alation Launches Data Governance App and Supporting Service Offering

Contributed by Matt Sullivant and Kartik Hansen

The importance of data governance is growing. Here at Alation, we’ve seen the demand for new robust governance capabilities skyrocket in the past year. To meet that demand, we’re excited to announce a new application and concomitant service offering, which together empower business leaders to lead governance efforts with clarity and confidence.

With this change, we seek to better tailor our solution to the precise needs of each customer. This will enable you to choose exactly the right mix of data catalog plus apps that best meet your business needs. And as we look to the future, breaking out capabilities into apps will empower us to develop those features more quickly to better serve you.

Alation Data Governance App

The Data Governance App introduces a range of new capabilities to make governance more easy and effective. Specifically, it simplifies how organizations enable secure access to the best data in today’s hybrid & multi-cloud environments. The App delivers autonomous data governance and accelerates the timeframe to customer success. Key features of the app include: a policy center, governance workflow, stewardship workbench, and governance dashboards.

• Policy Center: Create policies in one location and get complete visibility into how policies are mapped to data.

• Governance Workflow: Create and configure governance workflows right from within the app — all without coding or invoking other applications

• Stewardship Workbench: This feature uses AI and ML to automate the discovery of candidate data stewards based on who is actually using data.

• Governance Dashboards: With the governance dashboard, leaders can actively measure progress on open tasks, policy usage, and more.

Data Governance Service Offering

Data governance takes more than tooling alone; it also requires best practices. For this reason, Alation provides a service offering that includes an active data governance service offering, as well as maturity, and compliance assessments.

The service offering can start wherever customers are in their governance process. This is regardless of whether your goal is selling the value of analytics or responding to governmental regulation. Regardless of your business’ maturity level, Alation professional services kickstarts things by applying best practices that quicken governance deliverables. In addition, we can define your metrics and success measurements, so you know when you have achieved your desired business outcome.

With a strategy in place, we can help with policy definition, data rules process and decision rights, accountabilities, controls, and even putting together a data stewardship program.

Active Data Governance

For those wondering, “Why all the fuss over data governance?” Our answer is this: Data Governance Matters! The simple fact is every organization should practice data governance because it delivers data which is trustworthy, fit for analysis, secure, and compliant.

However, traditional data governance has been manual, top-down, and forced. This has left many asking whether the data governance journey is worth the cost in terms of time and people.

Alation today offers an alternative, non-invasive approach built on four principles:

1. Data governance should be people-centric versus data-centric;

2. Data governance should be deployed within a continuous improvement framework;

3. Technology should automate the drudgery out of data governance; and

4. When data governance is made easier, it is organizationally transformative.

These principles allow data stewards to do their day jobs while adding their invaluable perspective on data and how it should be used.

4 Key Benefits for Customers

Effective data governance is built upon the concepts of agile and continuous improvement. Data governance is not a “one and done.” It must be refined in a continual improvement process. Given this, data governance should be a key enabler of DataOps. For this to happen, the underlying technology supporting data governance needs to be built upon machine learning so the governance process gets better and better over time and requires less and less effort.

1. People First

In the past, data governance emphasized preventing people from doing things. A people-centric approach, by contrast, enables people to do things. Instead of mandating data governance from the top down, a people-centric approach works from the bottom up; it starts by recognizing existing organic data stewards and then automates tedious stewardship work over time. The goal is to make data governance no longer a burden or chore that is mandated on top of busy people’s existing schedules.

2. Autonomous Stewardship

Behavioral intelligence, machine learning, and automation accelerates each of the processes of data stewardship, including:

• Policy importation and creation

• Stewardship determination

• Curation

• Governance workflows

• Measurement processes

During each phase, intelligence makes the processes of data stewardship less and less of a chore for data stewards and those that support them.

3. Continuous Improvement

Business and technology leaders must improve the processes they oversee. This is not easy! But a new approach has taken hold. Business leaders have embraced agile, continuous development and CI/CD as a methodology that can transform a number of business processes. Inspired by the Japanese business philosophy of kaizen, meaning “change for the better” or “continuous improvement,” leaders have applied this system to a range of business processes successfully, in order to realize gradual change over time.

This methodology is now being applied to data governance. It improves governance processes and makes DataOps processes less constraining upon organizations. Modern governance practitioners recognize that governance is an ongoing, continuous process, with ample opportunity to improve and optimize at every step. New knowledge contributes to an ever-improving system, ultimately facilitating more autonomous (and successful) governance.

4. Deliver Expected Business Outcomes

In the end, data governance must deliver business outcomes through refining or protecting data. Speed is paramount. In today’s world, the goal should be to accomplish business ends faster. No longer can organizations take 10 years to get their data processes together.

In the past, only regulated industries invested in data governance, but that’s changing. Today, every industry should have conscious data improvement processes. Better technology can deliver on this without adding to people’s already busy jobs and schedules.

How Does Alation Automate Data Governance?

Active Data Governance begins by identifying key players. Leaders kick off the process by establishing a framework and identifying data policies that match your objectives. Once these are in place, assets are ingested, so that data groups (and top users within those groups) are identified.

For the first cycle through the process, top users are naturally people who should be recruited to be data stewards. However, in subsequent rounds of data stewardship where stewards are identified, the technology can auto-assign assets to responsible data stewards. Where intelligence does not identify data stewards, the stewardship workbench allows stewards to see unassigned assets by popularity of use and to either select themselves as a steward or suggest stewards for these assets.

With stewards assigned, asset curation processing can begin. Automation accelerates the process of populating, checking, and refining asset attributes. The goal is to create attributes for each asset as stipulated in the policies and standards. With this accomplished, data is ready for collaboration and reuse.

During this phase, as use increases, intelligence can automate more and more of the process. Once automation has been integrated, leaders can invoke user-friendly, native workflows to govern change or to escalate an issue.

Quality assurance is a key final step. Are policies being followed? Are data assets being curated at the right pace? Can measure curation progress against the policies and standards using analytics and stewardship dashboard reporting. With this insight, the process begins again by considering new policies.

Parting Words

Constant influx of data presents a range of opportunities — if a business is agile enough to see and seize them. For business leaders, the “aim should be to make a company agile so that it can create an innovative and constantly evolving portfolio of digital offerings.” (Ross, J., Beath, C., & Mocker, M. 2019. Designed for Digital, pg 15.) These businesses should have “ubiquitous data which means they don’t guess what customers want, or who they are, or whether they are loyal” (1).

We do not believe that legacy businesses can become agile when it takes ten or more years. This means reinventing what data governance is about and enabling business agility. It is time that the process was easier. It is time for all businesses to begin in earnest their data governance journeys. request a demo