January 6, 2021

Breaking Down the Data Language Barrier

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Breaking Down the Data Language Barrier

Over the last twenty years, data has replaced accounting as the universal language of business. Across industries and departments, teams rely on data to drive decision-making and optimize day-to-day operations.

When companies commit to a data-driven approach, it increases internal alignment, helps teams and departments collaborate, and allows everyone to see how their efforts are moving the needle and contributing to organizational objectives. As Ben Yoskovitz, founding partner at Highline Beta explains, “Data not only helps us figure out what to do, but it helps us understand why we’re doing it.”

Even more valuable are the powerful insights data unlocks. When companies are able to decipher trends, patterns and behaviors in their data, they’re able to develop winning ideas, strategies, and plans that catapult the business forward. In fact, insight-driven companies are growing 8x faster than global GDP.

But surfacing these transformational insights requires the collaboration and cooperation of two very different groups of people — those with data expertise and those with business domain expertise.

  • Data teams: For data to be useful, it must be collected, organized, and analyzed. Databases are complicated technical systems that require deep SQL knowledge. Companies employ teams of data engineers, data scientists, and data analysts to prepare data, explore it, and begin finding insights.
  • Domain experts: Accessing, manipulating and analyzing data is only half the answer. Data can only solve business challenges when teams deeply understand the problems and opportunities at play. Business domain experts have a fundamental grasp of these specific issues and are intimately familiar with their nuances due to years of experience in their respective fields.

Nobody knows it all, and it’s naive to think one group can successfully solve business problems and surface game-changing data insights without help from the other. Yet despite the obvious symbiotic relationship between these two groups, a data language barrier prevents them from working together effectively. The results are wasted time and resources, few to zero meaningful data insights, and missed opportunities.

In this survey report, you’ll discover why data teams and domain experts struggle with collaboration, the reasons the data language barrier exists, and what companies can do to harness the full value of their data.

About This Survey

Sigma commissioned Atomik Research, an independent creative market research field agency, to conduct an online survey of 801 data experts and 800 line of business employees from companies with between 201-10,000 employees within the United States. The margin of error fell within +/- 3 percentage points with a confidence interval of 95%. The fieldwork took place between March 2nd and March 9th, 2020.

Note: total percentages may not add up to 100% due to rounding

Executive Summary

Data experts and business domain experts both claim to be data driven but have different definitions of what that means

More than three quarters (76%) of survey respondents say their companies are somewhat to very data driven. When asked to define what being “data driven” means, 39% of domain experts admit they’re “not totally sure,” while only 6% of data experts feel the same.

Despite feeling confident about what it means to be data driven, data experts feel insecure about the results they’re able to deliver. Nearly half (45%) say they struggle to interpret domain experts’ data questions or needs. Domain experts seem to agree that the deliverables data experts provide are missing the mark. A fifth (20%) of domain experts report they rarely or never feel as though their data needs are adequately met by their data team.

Data experts believe they aren’t completely to blame for this. More than a third (36%) surveyed believe domain experts do not understand what can and can’t be done with data.

The data language barrier prevents companies from extracting the full value of their data

Communication gaps between data teams and domain experts are slowing down the organization’s ability to make use of data when it’s still fresh and at its most valuable.

More than half (55%) of data experts admit the average turnaround time for a data request is 1-4 weeks. When asked what causes these bottlenecks, 29% say it’s because too few data analysts support too many business teams, 28% claim C-level requests are given precedence over others and create a backlog, and 27% blame the bottlenecks on large data sets that are difficult and time consuming to curate and analyze.

Stuck waiting for data that doesn’t always address their needs, domain experts are quick to abandon their pursuit. A quarter (25%) admit they have given up on getting an answer they needed because the data analysis took too long.

Lack of confidence and low data literacy prevent teams from being data driven

Business domain experts lack basic data skills but are uncomfortable turning to data experts for answers. Some 34% reveal they are not confident in their ability to articulate data questions or needs to their data teams, and 30% admit feeling embarrassed by their lack of data knowledge.

Despite their shortcomings, the majority of domain experts recognize the value data can bring to their roles. Nearly three-quarters (71%) express a desire to improve their ability to understand and analyze data, and almost half (49%) think this could help them become 50-100% more effective at their jobs.

Unfortunately, domain experts feel their companies don’t support them in their quest to become more data driven. Almost half (48%) of all surveyed employees report their companies do not offer or do not make it clear that they offer any sort of data training.

Meanwhile, “fear of messing it up” is preventing 29% of domain experts from exploring data even if the tools to do so are available.

Data experts feel unappreciated and unfulfilled

More than a quarter (27%) of data experts report feeling unfulfilled or very unfulfilled in their roles. A major contributor to these feelings is the high volume of low-value ad hoc reporting requests, which take up a large portion of their time. Three-quarters (76%) of data experts say up to half (49%) of their time is spent preparing ad hoc reports for business teams.

These reports often grow in scope and spiral into never-ending projects. Over half (53%) of data experts reveal they receive up to 4 follow up questions for each fulfilled data request. After all the time and resources that go into preparing these reports, data experts feel their work is under-appreciated by company leadership, with 34% sharing they’ve felt unable to convey the value of an analysis to an executive or key decision maker.

Despite these challenges, data experts and domain experts want to collaborate more effectively

More than three quarters (79%) of data experts and well over half (64%) of business experts desire to work together more closely. For them to collaborate more effectively, organizations need to provide a common tool that allows both groups to make the best use of their expertise and participate in the data conversation.

Modern cloud analytics and business intelligence (A&BI) tools bridge the gap between data experts and domain experts. Connecting directly to cloud data warehouses, these tools offer visual, near real-time analysis of billions of data rows without the need to manually write SQL. A familiar and accessible interface, like a spreadsheet, serves as the common language and transforms A&BI into an iterative, community-driven process that allows both groups to explore data together, build on each other’s work, and surface powerful data insights.

Pressure to be Data Driven Is Causing Tensions to Flare

Across industries, executives are urging their teams to be more data driven. It’s no coincidence that the most innovative and profitable companies of our time put a strong emphasis on collecting, analyzing, and acting on data. The proof is in the pudding. Data supports better decision-making across the board — from hiring to operations to marketing strategy, to product purchases.

The desire to be, or at least be seen as, data driven is a uniting force for both data and business domain experts. Nearly half (47%) of all respondents say their company is data-driven or very data-driven, with 29% saying that their company is somewhat data-driven. But when pressed further about what it actually means to be “data driven,” the cracks begin to show.

Frustration, distrust, and insecurity

A whopping 39% of domain experts admit they’re “not totally sure” what being data driven means, while only 6% of data experts say the same. The rift between these two groups goes well beyond a simple disagreement over a definition — it permeates every facet of how they work together.

What does it mean to be data-driven at your company?
(Top 3 answers)

Organizations are spending huge sums of money building their data analytics programs and expect a strong return on those investments. Yet a quarter (24%) of data experts reveal they feel either not at all confident or not very confident that the reports and dashboards they or their teams deliver meet the requesters’ needs. And 45% admit their team often or always struggles to interpret business experts’ data questions or needs.

Each group seems to blame the other for poor collaboration. A fifth (20%) of domain experts report they rarely or never feel their data needs are adequately met by their data team. Data experts are quick to lay the blame on their less technical colleagues. Well over 1 in 3 (36%) surveyed have felt that domain experts don’t understand what can and can’t be done with data.

This misalignment, insecurity, and finger pointing does more than simply slow down an organization’s ability to extract value from its data. Left unchecked, it can take a serious bite out of its bottom line.

The Data Communication Gap Is Damaging Your Business

To stay competitive in today’s fast-moving global marketplace, organizations must continually uncover data insights. Sustaining this level of discovery requires the ability to collect, analyze, and act on data as fast as possible. Data has a shelf life. The CGOC estimates that 60% of data collected today has lost some—or even all— its business, legal or regulatory value. It’s no exaggeration to say that every second counts.

The data language barrier slows communication between domain experts and data teams, reducing the value of an organization’s data and inhibiting its ability to act on it. More than half (55%) of data experts and nearly a third (32%) of business domain experts say the average turnaround time for a data request is between 1 and 4 weeks — an eternity in the business world.

What is the average turnaround time for an average data request at your organization?

Data bottlenecks cause business experts to lose patience

Interestingly, executives recognize these bottlenecks while many employees either can’t see them or choose to ignore them. Two-fifths (42%) of individual contributors claim they don’t have any reporting bottlenecks in their organization, while only 11% of executives feel the same. This discrepancy may signify that individual contributors are lagging behind executives when it comes to making data-driven decisions and using data in everyday workflows.

Additionally, younger respondents seem more aware of existing roadblocks than their older colleagues. Nearly half of Baby Boomers (49%) report no reporting bottlenecks, while only 1 in 5 (18%) of their Gen Z workmates agree with them.

However, most interesting is the discrepancy between data experts and domain experts. More than half (51%) of domain experts say there are no reporting bottlenecks, while only 6% of data experts come to the same conclusion. This shines a major spotlight on the lack of understanding and alignment between these two groups.

Additionally, 25% of data experts cite slow SQL as a major contributor to bottlenecks, while just 4% of their business expert counterparts say the same. Opinions around the impact of urgent C-level requests, large datasets, and data experts being outnumbered by line of business teams also differ significantly between the two groups, further revealing that business experts are unaware of the challenges their data expert colleagues grapple with and/or underestimate their effects.

Which of the following issues cause analytics, business intelligence, and/or reporting bottlenecks in your organization? (Top 5)

Unable to get the data they need when they need it — and largely unaware of the bottlenecks causing this — domain experts grow frustrated. Some 1 in 4 (25%) domain experts have given up on getting an answer they needed because the data analysis took too long. About 1 in 5 (20%) admit they’ve had to guess when making an important decision because data wasn’t available in a timely manner. When data isn’t used, the time and effort spent collecting and preparing that data becomes worthless.


Have you ever done or experienced any of the following? Select all that apply.

To get a return on their data investment and benefit from the game-changing potential data insights can possess, companies need to understand the challenges both data experts and domain experts face and how to bridge the communication gap.

Fear and a Lack of Data Literacy Frustrate Business Domain Experts

Business domain experts have been challenged to take a more data-driven approach to decision-making, but are reluctant to turn to the people in the best position to help them do this: the data team.


How do you rate your personal data ability to analyze, interpret, and use data?

15% Data is like a foreign language to me and I don’t understand it at all.

28% I try but it’s definitely not my strong suit.

43% I’m decent at working with data but know I have room to grow.

13% I use data to make decisions on a regular basis and I am pretty good at it.

1% I consider myself a data expert!

Not being a ‘native speaker’ in the ‘language’ of data has caused many domain experts to feel self-conscious or intimidated. More than one-third (34%) are not very confident or not at all confident in their ability to articulate their data questions or needs to their data team/analyst. Some 3 in 10 (30%) domain experts have felt embarrassed by their lack of data knowledge or skills.

Perhaps frustrations among data teams regarding job fulfillment and perceived value (see the following section) are being reflected in the way they treat their business colleagues. Some 1 in 5 (20%) business domain experts report they have felt judged by a data expert due to a perceived lack of data knowledge.

The desire to learn is there; the resources are not

Business domain experts feel uncomfortable about their lack of data literacy. About 7 in 10 (71%) desire to improve their ability to understand and analyze data. While they may not trust their data expert colleagues, they do see the value data provides. Nearly half (49%) think they’d be 50-100% more effective at their jobs if they had a clearer understanding of data and how to use it.


Rate your desire to improve your ability to understand and analyze data.


How much more effective do you think you’d be at your job if you had a more clear understanding of data and how to use it?

The problem: While companies expect line of business teams to be data driven, they aren’t giving them the tools and training they need to achieve this goal. Over a third of all surveyed employees (35%) say their company definitely does not offer training to help them better understand and use data. Further, 13% aren’t sure if their company offers this type of training or not.

Interestingly, when the answers are broken out across data experts and domain experts, 73% of data experts claim their companies offer training to help with data literacy, compared to just 33% of domain experts. This is a strong signal that companies’ data learning resources are either too advanced or not relevant for business teams.

Does your company offer any sort of training to help you better understand and use data?

Paralyzed by fear

This lack of data literacy training and reluctance to partner with their data expert counterparts prevents business domain experts from even trying to use any data tools available to them. More than a quarter (29%) of domain experts say “fear of messing it up” keeps them from exploring data and using it more freely. Overall, adoption of business intelligence solutions hovers around a paltry 35%.

Business domain experts also feel pressure to know exactly what they expect reports to show before they request them from the data team. Because results can take weeks and involve multiple data team members to complete, they fear wasting time and resources. Ironically, this reluctance to indulge their curiosity, explore the data, and ask questions prevents them from taking the very actions that ultimately lead to insights.


Which of the following do you believe would help improve your data understanding, usage, and confidence? Select all that apply.

The solution:

  • Provide training to improve data literacy: Build confidence and improve data literacy by holding training sessions and workshops. Instead of making assumptions, conduct an internal poll to accurately determine which topics your business users want help with so you can address their needs directly.
  • Build and share powerful dashboards: A well-designed dashboard can answer many of business teams’ most pressing questions. But not all dashboards are created equal. Seek out visualization tools that allow business teams to get answers to follow-up questions by digging deeper into the underlying data — without having to rely on the data team for updates.
  • Give domain experts a safe space to explore: Business experts want to access data freely but are afraid of making mistakes that could put databases at risk. Unlike legacy BI and analytics tools, modern solutions like Sigma connect directly to your cloud data warehouse. Data is never moved, stored, cached, or copied, allowing both data and domain experts alike to feel more comfortable knowing that the data is always safely inside the cloud data warehouse.

Low Job Fulfillment and Fears of Being Undervalued Weigh Heavily on Data Teams

‘Data scientist’ was once called the sexiest job of the 21st century, and it’s easy to see why. With the highest starting salary in the country, loads of top tier companies hiring, and the chance to help organizations solve complex and interesting problems, you’d think those in this role would boast high rates of job satisfaction.

Interestingly, more than a quarter of data experts (27%) report feeling unfulfilled or very unfulfilled. These feelings largely stem from disappointment over what they imagined themselves doing in their roles versus the reality of their day to day work.


How fulfilled are you by your role and day-to-day activities?

Trapped in report factory hell

More than three quarters (76%) of data experts say between 20 – 49% of their or their team’s time is spent preparing ad hoc reports for line of business needs. Ad hoc reporting is essential for the agile enterprise, but problems arise when domain experts have to rely on data teams to do this data exploration for them. With data questions and needs coming from multiple parts of the business, data teams find themselves scrambling to prioritize these requests and balance their workloads.


How much of your or your team’s time is spent preparing ad hoc reports for line of business?

The report queue often feels like it never ends. About 53% of data experts reveal that they receive between 3 and 4 follow up questions after an initial ad hoc request is fulfilled. Data teams feel trapped in report factory hell, with little time for higher value data projects that lead to greater personal fulfillment.

On average, how many follow up questions do you or your team receive after fulfilling an initial ad hoc data request?

Misunderstood and underappreciated

Another source of frustration is a perceived lack of appreciation from executives and senior leaders. A third (34%) of data experts have felt unable to convey the value of an analysis to an executive or key decision-maker.


Have you ever felt any of the following? Select all that apply.

32% Frustrated by the larger organization’s lack of data knowledge or expertise?

34% Unable to convey the value of an analysis or subsequent recommendation to a executive or other key decision-maker

36% That line of business experts don’t understand what can and can’t be done with data

27% Undervalued and underappreciated for your data expertise?

Once again, the data language barrier is largely to blame. Domain experts often have an incomplete understanding of how data is collected, organized, and analyzed. They’re prone to assumptions about how much the data team understands about a problem and what data they have access to.

When results are delivered, they may misunderstand or oversimplify the analysis, leading to frustration among data teams striving to meet the high expectations placed on them. Nearly one third (32%) of data experts say they’ve felt frustrated by the larger organization’s lack of data knowledge or expertise.

This lack of data literacy among business experts is stoking fear in data teams and fuels reluctance to open up data access to the entire organization. Misuse or misinterpretation of data account for the top four fears data teams have about making data more accessible. Only 5% of data experts say they have no fears about opening up data access.


What are your main fears or concerns when it comes to making data more easily accessible to the larger organization? Select all that apply.

When employees feel misunderstood, undervalued, and unappreciated, productivity suffers, turnover increases, and valuable insights remain untapped.

The solution:

Data teams need to be freed from tedious, manual work so they can focus on higher value projects that help businesses reach organizational goals and lead to greater job satisfaction. This can be accomplished through a three-pronged strategy:

  • Enable everyone to explore: Invest in tools that enable true self-service analytics and business intelligence to cut down on the number of incoming requests. Solutions with familiar user experiences and visual analysis capabilities fuel adoption and empower business domain experts without coding abilities to explore data on their own. Tools like Sigma have helped data experts free up to 50% of their time by minimizing ad hoc requests and endless back and forth.
  • Focus on the work that matters: By empowering domain experts to explore data themselves, data teams are free to pursue higher-value work for their organizations, like uncovering new data sources, building new data models, and solving more impactful problems.
  • Build a strong data governance strategy: Turning over data access to domain experts can feel scary to the seasoned data team, but freedom and flexibility doesn’t have to come at the cost of security or control. Look for tools that sit on top of your existing cloud data warehouse and don’t require storing data locally so you can eliminate vulnerabilities caused by data migration or extracts. Solutions with access controls and robust permissioning help data teams maintain security standards while still meeting the organization’s needs.

With this newfound free time, data teams can shift their focus to higher ROI data projects that advance business outcomes. Success will no longer be measured by the number of reports they create for business teams but by the value they deliver to the organization as a whole.

Fortunately, most data experts we polled know exactly where they would invest their free time. Some of the top responses included:

  • Strategically planning how the company can better use data
  • Doing more complex and highly impactful analysis
  • Optimizing or updating underlying data infrastructure and technology
  • Building more comprehensive and robust data models


If you or your team no longer had to spend time creating basic dashboards and reports for line of business teams, which of the following areas would you focus on? Select all that apply.

When domain experts are free to independently explore data and data teams are unencumbered by ad hoc reports, each group is empowered to put their expertise to use. This results in higher job satisfaction, faster time to data insight, and greater collaboration.

Both Data Experts and Business Leaders Are Eager to Bridge the Gap

Despite the data language barrier and the friction it creates between them, both data experts and business domain experts seem to recognize what the other group brings to the table.

A 2017 report revealed 60% of data analytics projects fail because they weren’t aligned with the business strategy. This is unsurprising given the communication rift that exists between business leaders and data teams. Almost half (46%) of the data experts we spoke to admit that their or their team’s lack of business domain expertise often or always gets in the way of delivering the most accurate or relevant data models and/or reports.


Data experts, how often does your or your team’s lack of domain expertise (e.g., Salesforce field definitions, key marketing metrics, etc.) get in the way of delivering the most accurate or relevant data models and/or reports?

This pain is more acutely felt by younger data experts than older ones. Baby Boomers entered the data science world in its infancy, often making the transition from other fields. In contrast, their Millennial counterparts entered directly into a much more mature and established data science industry.

This cross-functional experience has helped make Baby Boomers more confident in their ability to aid business teams. Half (49%) of Millennial-aged data experts lament their teams lack of domain expertise, while less than one third (28%) of their Baby Boomer-aged colleagues feel the same.

Better together

Transformative data insights require marrying data knowledge with domain expertise. The waterfall approach of chucking vague requests at data teams and then expecting them to define the problem, identify the correct data, and then work out the solution is setting them — and by extension the business — up for failure.

The good news is both groups see the need to work together better. Four-fifths (79%) of data experts want to collaborate more closely with their lines of business colleagues, and 64% of domain experts feel the same way about data experts.

If the desire exists, what’s holding them back? It boils down to a lack of shared understanding and shared language.

The solution:

Bridging the gap between data experts and domain experts is easier than one might think. Both groups are eager to take a more collaborative, community driven approach to analytics:

  • Build empathy: The first step is building empathy between each group. We develop empathy through learning what another person’s work entails, and building off a shared understanding of both problems and possible solutions. Host workshops, lunch and learns, and mixed team exercises to break down communication silos and get people working together. When both groups of people can share their expertise on an equal footing, respect and empathy grow.
  • Take a community-driven approach to data processes: Data is a team sport and should be community-driven for the best results. When everyone can share and build on each other’s work, innovation prevails. The time to value and data ROI is accelerated exponentially when teams can explore data across departments and applications, uncovering new connections, trends, and insights. Seek out modern BI tools like Sigma that allow true collaboration between data and domain experts through features like collaborative data modeling, a common spreadsheet interface, the ability to write views back to the data warehouse for use across the full data ecosystem, and more.
  • Get everyone speaking the same language and using the same tools: Data is the common language that everyone in an organization can and should be able to speak. The humble spreadsheet has proven itself to be the preferred data insights conduit for both business and data experts, with 85% of people using spreadsheets in their work. And even amongst people that understand and use SQL, 88% still turn to a spreadsheet when exploring data. A new generation of spreadsheet-inspired tools like Sigma are helping domain experts quickly jump in and collaborate through data.

A Barrier Meant to Be Broken

The language barrier between data and domain experts is significant, but not insurmountable. Both groups share common goals and desired outcomes:

  • They both want to solve business problems.
  • They both desire to collaborate with each other.
  • They both need to explore data in a way that’s accurate, safe, and easy.

To achieve these results, both groups must work together to close the communication gap and collaborate more effectively. Transformative insights come from the marriage of data knowledge and domain expertise.

Sigma is the universal translator that breaks down the data language barrier and enables everyone to participate in the data conversation. Using the Sigma Spreadsheet, data and business experts can work together to ask questions, get answers and drive results. It’s a powerful yet approachable tool that allows both groups to benefit from each other’s unique expertise and explore data together.

Let’s Sigma together! Schedule a demo today.

We are Sigma.

Sigma is a cloud-native analytics platform that uses a familiar spreadsheet interface to give business users instant access to explore and get insights from their cloud data warehouse. It requires no code or special training to explore billions of rows, augment with new data, or perform “what if” analysis on all data in real⁠-⁠time.