The role of the CDO will not suffer the slow rise to prominence other emerging C-level roles have seen in previous years. Modern technologies designed to easily centralize, access, analyze, share, and monetize data have arrived. As a result, data has become the most powerful resource to drive an organization’s transformation. That puts CDOs at the wheel, their foot on the pedal, and their fellow execs holding on tight for the ride of their lives.
Here are the top trends in 2023 I think CDOs should look out for and capitalize on. Otherwise, instead of taking the wheel you could be riding at the back of the bus.
The role of the CDO will be better understood
In 2023, C-level execs and LOB managers will realize the true impact of the CDO role and the impact it could have in organizations. But CDOs must drive this mindshift by exposing their colleagues to what’s now possible with data that wasn’t possible just a few years ago.
The death of the data silo will pick up pace
Allowing the many apps and other solutions organizations use to capture and imprison data will dissipate at a quicker pace. The ability to easily centralize all of this data and deliver previously unobtainable insights has arrived. Leading organizations are now creating a single store of data from dozens (and even hundreds) of apps located on-premises and in the cloud. From start-ups to global corporations, access to near-endless insights will drive efficient operations, amazing customer experiences, and new business opportunities.
Monetizing data will rise from the cellar
Data monetization is a distant third as a data priority for most organizations. But CDOs will continue to streamline and normalize their first and second priorities: delivering business initiatives based on data, and data-literacy programs designed to educate their organizations. As such, the opportunity to monetize data will emerge more prominently and thanks to modern data sharing and collaboration technologies. This will create new revenue streams and connect their organizations to the data economy.
The infrastructure for data science will be platform-based
Too many niche solutions exist for developers and data scientists to use, and these solutions are disjointed from centralized data storage. The pressure to consolidate data science operations and be more cost-efficient will cause data science and ML models to be built via cloud data platforms. The data science community will embrace all-in-one platforms, so they can avoid moving data out of repositories, into these separate tools to build and train their models, and then move that data back again. A single platform approach will also enable built-in governance capabilities to achieve classification, RBAC, cataloging, data quality, and observability. It’s insane to endure the cost and complexity of using disparate tools. Instead, developers and data scientists want one platform and one infrastructure, where data doesn’t have to move.
Business intelligence (BI) folks will graduate to become data scientists
BI professionals need to adopt Python and other languages, and move from simply visualizing data on a dashboard to building data applications. Why? Business users no longer are restricted to simply consuming results provided to them. Instead, they need a self-service solution so they can easily run a multitude of queries on the data to understand not only what happened, but why it happened, how it can be prevented, and what is yet to come. Application frameworks in a single environment with flexible tooling that enable apps for data science and ML will help graduate BI folks to become data scientists.
Data science will start to permeate every department in an organization
Looking at the past with business intelligence data is no longer enough to compete, let alone remain relevant. The most modern organizations are looking forward with predictive and prescriptive analytics enabled by data science, ML, and the ability to efficiently crunch massive amounts of data. From Sales and Marketing to Corporate Finance, these departments are deploying their own data science teams to determine their future.
Easily developing data-driven apps will change the face of SaaS
The multitude of SaaS solutions available can help automate many LOB functions, and many of these provide sufficient analytic capabilities. But there are gaps, where features and functionality to help advance a business are missing from these solutions. Commercial SaaS offerings are designed for general purpose and are often deficient in supporting specific needs and therefore require deep customization. Or, the solution an LOB needs simply doesn’t exist. With today’s cloud data platforms and powerful yet simple development environments, organizations can easily create their own solutions to meet their specific needs. That means they can also commercialize and monetize these apps.
The consumption-based business model will begin to emerge as the new norm
CDOs and other execs are under the pump to get value for money. Translation: use what you buy, so buy only what you need. Accepting this modern business model hasn’t been an issue. But implementing it has been because the technology wasn’t available, until now. The technologies and access to requisite data to run an organization based on consumption are ushering in the most efficient businesses possible. Case in point: Organizations will have access to easy-to-use tools to predict their SaaS usage and future spend on these solutions. No longer will LOBs underutilize and overpay for SaaS subscriptions.
These trends will quicken their pace in 2023 and in the years ahead, revealing much more than organizations ever thought possible. But the strategic business opportunities for CDOs and their organizations that lie ahead will be truly spellbinding. So strap in, shift into high gear, and hit the fast lane.