How Independent Talent Can Help with the Latest Data Management Trends

Today, data is and should be top of mind for business leaders in every industry. With the amount of data coming and going every day, it’s no surprise that the need for data management specialists has also skyrocketed. BTG’s recently released 2022 Skills Index bears this out, showing data management to be the 9th fastest growing independent talent skill with an increase of 82% in project requests YOY. As companies increasingly embrace technologies that rely upon structured data—such as the internet of things and artificial intelligence—holistic data management has become a corporate necessity.


Data is constantly being generated, accessed, and processed in today’s always online and increasingly connected world. On the personal level, it could include user data on your browsing history and online platform interactions, cookies that enable seamless logins and targeted advertisements, facial recognition to unlock your devices, and much more. At the corporate level, there’s a lot that goes into securely capturing, storing, and harnessing data for business impact, such as:

  • Data governance and security
  • Database architecture and data warehousing
  • Analysis and business intelligence
  • Data quality and integration

And that’s only a small sample of the tasks required of companies to maximize the utility of their data and generate actionable insights. Yet, research shows that as much as 85% of time is spent on data prep and only 15% is spent on actual analysis. Moreover, only 25% of companies feel like they are exactly where they want to be in their corporate data management—down from 31% in 2015. The need for structured and actionable data has become more acute and with it a realization that previous models of data management are no longer up to the task.

Today's Top Data Management Trends

As data management increases in necessity, there are some breakthrough trends worth noting, including data monetization, artificial intelligence (AI), data “lakes,” and data democratization. These in no way encapsulate the entirety of data management but are especially critical for business leaders and consultants in the industry today. What do they have in common? They all demonstrate how companies are seeking to make data a core asset of the business.

Monetizing Data

In a recent Business Talent Group (BTG) Expert Q&A, data strategy and transformation leader Bill Sequeira discussed three ways companies can monetize data—via a data-driven service, a product enabled by data, or data as an asset in and of itself. Each of these areas requires a different set of tasks and considerations to implement properly.

Sequeira said, “As data use becomes widespread, the risks of cyber injury (the consequences of using online data against someone), cyber liability (exposure to liability through the use of data), and the use of ‘fake’ data in data-driven systems will increase,” which is why the frameworks surrounding monetized data, such as compliance, privacy, governance, security, data breaches, and data leaks, must be considered on a regular basis.

We see data become monetized regularly—think business contacts, email lists, consumer analytics, and more. If it can be logged and monetized in some form or fashion, an independent data management expert can help your company develop a strategy and processes to do so.

AI and Data

What role can AI play in ensuring the quality and utility of data? While the field of AI is developing rapidly, it’s not yet a silver bullet on its own. According to Sequeira, “Good data requires good interpretation, and the challenge is having the right context for a correct interpretation.”

For instance, it’s quite possible that if you add the wrong parameters, good data could unintentionally be filtered out by default (until AI becomes intelligent enough to differentiate quality from lackluster data). The only way to avoid this misstep is to reject automation and allow a human analyst to review every possible data decision, which simply isn’t feasible at enterprise scale. Sequeira emphasized that if implemented correctly, however, AI can play an active role in detecting data that is prone to ambiguity, flagging abnormal cases, isolating conditions, and understanding patterns of use—resulting in higher quality data and AI being of greater value to all.

Data Lakes

A ‘data lake’ refers to a storage repository that holds a vast amount of raw data in its native format until it is needed, often binary large objects (BLOBs) or files. Though data lakes can present processing problems, they can be extremely valuable in the right situations. How can these lakes yield actionable insights? Sequeira points out that the value is not just in the data itself, but also in the algorithms integrated within data lakes. His advice for business leaders is to “seek data lakes that can provide a distributed, virtual view of data within your organization and can rapidly integrate new repositories into their standardized flow.” Having the ability to integrate disparate data sources rapidly and on-demand is critical.

Data Democratization

Data democratization is the process of making digital information accessible to the average non-technical user of information systems, without needing IT to step in—a process that leads to faster decision making and more agile teams. When data is readily available through self-service across the company, users become more comfortable working with data, more confident discussing it, and more adept at making data-driven decisions in order to build customer experiences powered by data. “The goal is to have anybody use data at any time to make decisions with no barriers to access or understanding,” says Bernard Marr, bestselling author of “Big Data in Practice.”

Getting everyone on the same page is crucial, but it’s no easy task. According to CompTIA, levels of satisfaction with data capabilities vary widely throughout the hierarchy of an organization. While 41% of those at the executive level report that they feel their company’s data capabilities are exactly where they should be, only 23% of IT staff feel that their data capabilities are ideal, likely because they are the most aware of areas for improvement. Finally comes business staff, with 17% reporting the highest level of satisfaction. This group is the most likely to understand the shortcomings of a subpar data approach because they generally are the ones tasked with pulling together insights, yet they tend to have the least access to data from all parts of the organization.

That was the problem faced by a major agriculture conglomerate that recently came to BTG in need of support for enterprise-wide data improvement. With the help of a Big Three consulting firm, the executive team had crafted a strategic roadmap for IT, sourcing, tax, treasury, and finance, and begun to integrate this work with the company’s broader business unit strategies and goals. The project’s owner, the Head of Global IT, needed help coordinating workstreams, synthesizing data, and making sure each business unit got the most out of the consulting firm’s recommendations. BTG provided a former McKinsey Associate Partner who worked with each business unit to document their processes and then used the consulting firm’s framework to craft an actionable plan for improvement. By the end of his engagement, he’d helped each business unit owner realize the full value of the original roadmap, increasing efficiency and ensuring strategic success.

The bottom line? Businesses can harness the power of data at all levels of the organization to improve the baseline of knowledge, decision-making, and, ultimately, the customer experience and business success.


With further data-reliant innovations—such as the implementation of AI-augmented analytics and self-service data management tools, monetization of corporate data assets, and adoption of distributed ledger technology for everything from supply chains to finance—already in the works, top companies are embracing new ways to stay ahead of the digital divide. In this environment, on-demand professionals are becoming an ever-more important source of in-demand data management skills.

Only 44% of companies say they have internal IT employees dedicated to data management or analysis, so it’s no surprise that 33% cite data-related skill gaps as a significant stumbling block. Without critical data management skills, digital transformations stall, growth stagnates, and projects fall by the wayside. But those hard-to-find skills are within reach in the on-demand market, and companies are increasingly reaping the rewards—finding skilled leaders to tackle projects like:

  • Developing and implementing policies, processes, and metrics to drive the accuracy, integrity, and timely creation and maintenance of supply chain and operations data
  • Creating an overall corporate customer data strategy, architecture, and implementation roadmap for database management
  • Translating top-line goals into actionable data points and synthesizing the information into a broader strategic roadmap that empowers company-wide data-driven decision making

Not only can independent talent be a source of hard-to-find digital skills, but the on-demand talent market also offers companies the ability to find perfect-fit “unicorn” talent with industry-specific experience and niche expertise. Instead of sourcing simply a general data specialist, companies can access experts with the exact combination of data management skills, industry experience, and working style needed. And if that perfect person doesn’t exist, the unbundled nature of on-demand talent allows for the creation of superteams that pair highly skilled data management talent with another expert possessing the specific industry or functional knowledge required for the project in question.

Moreover, with the increasing acceptance of remote work, companies are no longer limited to the candidate pool in their specific geographical area. Consider this stat from Coursera: “US digital skills proficiency falls behind that of many countries in Europe and Asia. 91% of US businesses accelerated their digitization plans in 2020, but skills among the workforce have not transformed at the same pace.” Opening your mind to the possibilities of remote independent professionals allows you to find the best possible talent for the project period, not just the best talent near you.

But companies shouldn’t have to go it alone when trying to find the best available talent for data management projects, especially when such experts are so difficult to source in today’s labor market. With BTG, you get a partner experienced in curating, vetting, and compliantly delivering the perfect talent for this critical work. With so many opportunities riding on these future-focused initiatives, having a trusted and knowledgeable partner on your side can be invaluable.

Ready to find a data management expert? Explore a project today!


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