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Zaloni 2022 Predictions: Thought Leaders Share Data Management Industry Predictions

vmblog predictions 2022 

Industry executives and experts share their predictions for 2022.  Read them in this 14th annual series exclusive.

Zaloni Thought Leaders Share Data Management Industry Predictions

2021 has been undoubtedly a year of growth as the industry continues to build upon the changes and new normalcy brought about the year prior. Data is at the center of everything. It's the most valuable asset for any company in any vertical, so learning how to properly manage data is a critical component to success. Year after year, the ways companies manage their data need to adjust and adapt to meet the needs of their current and future use cases. Ultimately, the new year holds a lot of progress for the digital and data spaces around data governance, self-service access to data, and automating data management tasks. A few of Zaloni's thought leaders are well-versed in the data management space and have curated their industry predictions for the upcoming year below.

Ashwin Nayak, VP of Engineering

1.  The Defining Year for Quantifying Data Governance ROI to the C-Suite

Historically, the c-suite, especially the CDO role, hasn't perceived data governance investments as a strategic value-add, largely due to a lack of well-defined, tangible measures of success. That will change in 2022. Establishing KPIs to link data quality to ROI, measuring usage metrics of data assets, and implementing policies to protect data are the missing elements in communicating the value of governance investments. The data protection initiatives require partnership with CIO to define policies, but the implementation will fall under CDO organization. Identifying data usage, history, access levels, sources, and endpoints across different applications and databases with search-based knowledge graphs will be a strategic priority for end-to-end observability. When organizations begin connecting governance KPIs to business value, it will inevitably lead to opportunities to activate and leverage their data to drive competitive advantage.

2.  Data Marketplace: Combining private data with public data marketplace to drive faster analytics

Data sharing was re-defined by leading industry providers, and today there is a strong push towards data marketplace and data sharing capabilities. The technology and tool set have come a long way, but there is still a gap in the marketplace i.e. enabling organizations to identify relevant data, out of thousands of data sources from the marketplace, in context to private data they own, and bringing them together in a secure, governed and self-serve way. Historically, this kind of use cases are solved by building pipelines and organizations invest resources to bring public dataset into their environment. In many cases, they find that the relevancy of data and impact in terms of reach or business value may not be tangible which leads to waste of resources. Organizations are becoming innovative by validating public data by cataloging, profiling, and validating with private data assets before making investment decisions.

Susan Cook, CEO

1.  Empathetic CEO Leadership Will Profoundly Impact Employee Well-Being & Productivity

A company cannot perform well if its employees aren't in a proper headspace. Our current climate is clouded with a global pandemic, economic turmoil, civil unrest, and other anxieties. Business leaders must lead by example and sincerely check in on their employees. Understanding how big of a role external factors play in employee emotional health is essential as their well-being is linked to overall performance and productivity. CEOs and managers incorporating more empathy into their leadership style will leave employees with the support that will positively impact their professional lives.

2.  We've only seen the tip of the iceberg with solutions that increase faith and trust in data.

We've only seen the tip of the iceberg of technology solutions that are truly able to handle data accuracy and relevancy. In 2022, we will leverage machine learning and automation more fully to manage, govern and improve data. Once we do that, enterprises will have more trust and faith that they have good quality data, which will result in much faster and better decisions.

Matthew Monahan, Director of Product Management

1.  Data Access Will be Accelerated by Automation

Organizations are laser-focused on replacing labor-intensive data management and data governance tasks with automation. By automating processes, accelerated access to data for data citizens is on the horizon. But this, like many things, has been accelerated by pandemic: open headcounts and newer employees means organizations will be looking for value at every turn. Rather than filling vacancies with salaried employees, companies will look to automate, making data more accessible.

2.  Data Governance Will Rely on MLOps

The best ML technologies have well-defined training sets and MLOps techniques to identify data at the right time, from the development process through training and testing. This MLOps transition parallels what we see in DataOps and what we saw with DevOps: you need to have good metadata to accomplish those processes. In the coming year, we will begin to see more crossover between data governance and MLOps because you need not just high-quality source data but also metadata to describe the data to feed into the MLOps process for development, training, and testing of those algorithms.


Published Wednesday, January 12, 2022 7:35 AM by David Marshall
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