CSpring’s Chief Data Officer and Executive of Delivery, Mike Butler, shares his top 10 trends to expect as we head into 2023.

Despite a recession looming on the horizon, there are no indications that digital-first, and therefore data-first, initiatives are slowing any time soon. Data and analytics topics will likely remain among business leaders’ top issues. Following are a few trends that I believe could be important for the coming year:

1. Increasing Shift to the Cloud for All Things Data

The cloud continues to be the place to do all things data for large enterprises and small ones alike. Small enterprises use cloud features, such as those in Snowflake, to reduce their need for on-staff DBAs and infrastructure support. Many larger data tech companies are no longer building technologies for on-premise data centers. Recession concerns will likely increase cloud adoption to keep costs as operational expenses and to avoid capital commitment, which reduces risks and exposure from innovation initiatives.


2. Increasing Talent Demand

The talent needs to support data initiatives and digital transformation will continue to increase through 2023. While AI will help analysts become citizen data scientists, leveraging recommendation tools and automatically generated code, the demand increase will come from those that understand data, understand programmatic thinking, and have increased data literacy. Both data storytelling, which involves creating a compelling narrative and communicating insights, and data engineering, will be two of the most challenging skills to find and retain.


3. Increasing Volume, Variety, Velocity, and Veracity of Data

Data has only continued to increase in the 4 Vs, and in 2023 this trend will not slow down but continue to accelerate. Driven by IoT and edge computing, data volumes will continue to grow at an ever-increasing rate. Streaming data, limited to a few industries, will become more critical for companies in digital transformation, in which custom customer recommendations and context have become critical to compete.


4. Increasing Demand for Data Democratization

Data democratization, which involves making data accessible to and comfortable for all employees, will become increasingly important as companies seek to empower their teams to make data-driven decisions. Data democratization will drive the need for better governance and work on solutions such as “reverse ETL.” With the simplification of tools and many new market entrants, 2023 is staged to see data democratization like we’ve not seen before.


5. Increasing New Market Entrants

The number of players in the market will continue to increase as barriers to creating AI and analytics tools decrease. The market is also becoming more saturated, so we don’t expect to see a single organization take over the market. I expect, based on the time-series model depicted below, to continue to see new players and new technologies. The data for this graphic, was collected from the United State Census Bureau and a shows historical trend of increasing growth in applications. Notice that a large increase has occurred just since COVID.


6. Increasing Need for Data in Automation to be Competitive

Companies will continue to identify opportunities to keep employee headcounts stable and automate where possible. The primary drivers for these opportunities are efficiency, cost savings, and freeing up employees to perform more value-added work. Automation requires data architectures that support the manipulation and management of information, which will lead to more significant data solutions and interoperability needs.


7. Decreasing Complexity of Enabling Organizations with ML/AI

Machine Learning (ML) and Artificial Intelligence (AI) systems are becoming easier to use. Tools such as Alteryx, PowerBI, Tableau, and others empower users with AI and ML tools while requiring little custom code. The low-code movement is empowering employees with technologies beyond their reach ten years ago. This decrease in complexity is poised to significantly impact the industry and the adoption of AI.


8. Increasing Use of Data for DEI, ESG, and Other Programs

Large corporations continue to implement DEI (Diversity, Equity, and Inclusion), ESG (Environmental, Social, and Governance), and other programs that require data. As companies lift off in 2023, they’re looking to track and understand their impact on their communities and brands. To accomplish this task, external data and information must be considered for ingestion into corporate data stores to create a single pane of glass for initiatives.


9. Increasing Bias in Data Will Make AI Training More Difficult

The 4 Vs (Volume, Variety, Velocity, and Veracity) continue to drive information into our storage repositories, but with this drive comes more biased data. Data collection and scale are bringing new levels of bias and contextual problems, which creates bias in models. The increasing reliance on web sources means bots and other tools, as well as biased humans replicating ideas, will have a significant impact on data validity. Companies will need to include model validation and data bias cleansing in their data governance programs. Assuming an increase in the use of AI tools, we’ll likely see an increase in the use of data in those tools by untrained teams. Those teams will need to be given the training necessary to succeed in developing analytics tools and removing data bias.


10. Demand for Digital Transformation Remains Stable

While digital transformation efforts will continue to be necessary, I expect the demand to remain stable with little movement. This demand stability is the result of industries reevaluating the owner of digital. Ownership is shifting away from technology leaders such as CIOs and CTOs and moving towards business leaders to drive transformation. This ownership shift, coupled with the uncertainty of the economy, will likely play out as stable demand for these services. One thing to note: To bridge the need for business transformation and the underlying data architecture needed to do it, companies without a chief data officer, may be challenged to meet the drive from the business.

2023 is poised to be a tough year. CSpring is here to help! For more information on what CSpring can do for you, be sure to reach out here!

Mike is an energetic technologist that values helping people navigate uncertainty and solve problems. As CSpring’s Chief Data Officer and Executive Director of Delivery and Innovation, Mike leverages his background in digital transformation to design practical, innovative solutions. He likes to share information and humor found in his blogs about cloud, data engineering, fraud analytics, cognitive bias, innovation, and leadership. It comes naturally for Mike to put himself in our clients’ shoes, having served as an engineer, analyst, developer, director, architect, strategist, and CTO in publicly traded financial services companies for nearly 20 years prior to joining CSpring. Mike has a proven history of building teams and technology to maximize business value. Mike holds a BS degree in management information systems and an MBA from Ball State University. He currently serves as a volunteer for the Information Systems and Business Analytics advisory boards at Ball State, where he is an active mentor for students. He and his wife Abby live in Muncie, IN, with Chloe, their affable cat.

The views and opinions expressed in this blog are those of the authors and do not necessarily reflect the official policy or position of the company. The predictions and forecasts made on this blog are based on the authors’ best estimates and assumptions and are subject to change without notice. The accuracy of the predictions and forecasts cannot be guaranteed. The authors will not be held responsible for any errors or omissions, or for any actions taken based on the information provided on this blog.

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