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