Big Data Fears & Predictions

What are the expectations of big data in 2022? Read about business leaders and data professionals' fears and predictions for big data.
Big Data Fears

Big Data in 2022

Key Findings

  • 64% of business leaders expect companies’ big data budget to increase in 2022.
  • 48% of companies are looking to hire data analysts in 2022.
  • Business leaders spend 12 hours a week, on average, working directly with big data.

If you’re worried about your data, you’re not alone: 40% of the business leaders who handle your data are worried about it themselves. Yes, a very sizable chunk of those in charge of data, in our most recent survey of data professionals, have confessed to feeling “very concerned” with the security of their company’s data. And in the age of rampant data-sharing, your data could very well be their data.

The recent conversations we had with hundreds of data professionals, including business leaders with data experience, led to more eye-opening insights than that, however. We got their industry insight into what their plans are for this year with regards to big data, what’s frustrating them the most, and how they keep on top of such a quickly changing industry. Keep reading to uncover their key takeaways.

Biggest Data Troubles for Business Leaders

For many, big data is as big and intimidating as its name. This first piece of our study asks business leaders what parts of it they find to be the most intimidating. The top ten specific challenges they face are also featured here.

For most business leaders, the most intimidating part of the entire data experience is the analysis itself. Analysis refers to the practice of actually working with the data in order to find information that’s truly useful. Leaders were right to admit that this part is complex. A full-time data analyst in the U.S. currently earns $70,000 annually, or roughly $20K more than the average American salary. More than half of the business leaders we spoke to also said they plan on hiring one such data analyst in 2022.

Analysis was certainly not the only challenge for business leaders and data, however. The collection of the data and implementation of the findings were also rated as very intimidating. And when asked about their top challenges, 44% mentioned how big data is constantly changing. Forty-three percent cited the sheer volume of data as a challenge, while another 40% mentioned the inaccuracies present in the data. Perhaps these many headaches are what have encouraged business leaders to consider outsourcing this year.

Annual Targets for Business Leaders

Again talking to just the people in charge of leading and growing businesses, this piece of our study asks about their specific plans for big data during the upcoming fiscal year.

Most upcoming strategies for big data were growth-oriented. Seventy-four percent of leaders answered that the data they have will mostly be used to identify areas and opportunities for growth. Many others (69%) wanted to use the information to help shape the customer experience, while 61% said big data will help them create operational efficiencies in 2022.

After acknowledging the hurdles of working with big data, we also asked respondents what their plans were to overcome these challenges. Most answered with intentions to start training their employees in order to support a big data program. Forty percent figured they would likely have to spend more on software that would help them manage big data. While the number of companies that store their data in the cloud has typically been increasing, there are many reasons for enterprises of all sizes to consider specialty storage options for security reasons.

Spending on Data

The most frequent data-oriented plans—training and spending on software—do not come free. So we decided to look at the budgets our respondents’ businesses anticipate for 2022 with regard to data.

Big data presently consumed a big portion of business leaders’ company budgets: A substantial 30% of budgets were reportedly allocated to big data, on average. Bear in mind that the vast majority (64%) were also expecting to increase their spending in this area, showing just how much value big data holds for these institutions.

Within the data field, the top positions leaders hoped to fill this year were data analysts (48%), data scientists (44%), and database managers (36%). A data analyst is someone who works with existing data to pull meaningful information, while a data scientist is someone who creates new ways of extracting the data in the first place. Data scientists also have a much higher earning potential, earning upwards of $100,000 annually.

A Day in the Life of a Data Professional

With so many businesses looking to hire data professionals, we thought we’d reach out to those who identified as such. In this piece of the study, data professionals describe their current roles and frustrations.

In spite of the high salaries and high demand, the life of a data professional isn’t always fulfilling. Of the 233 that we spoke to, 40% described their current jobs as repetitive, while 39% called it stressful. Their top workplace frustrations were repetition (48%), short deadlines (44%), and the sheer volume of data (38%). Additionally, roughly 1 in 3 data professionals reported working longer than the typical 40-hour workweek.

Staying Relevant as a Data Professional

Business leaders previously shared that one of their major frustrations with big data was how quickly it all changes. In order to keep pace with their own careers, data professionals shared a few tricks they had up their sleeve.

For most business leaders, the most intimidating part of the entire data experience is the analysis itself. Analysis refers to the practice of actually working with the data in order to find information that’s truly useful. Leaders were right to admit that this part is complex. A full-time data analyst in the U.S. currently earns $70,000 annually, or roughly $20K more than the average American salary. More than half of the business leaders we spoke to also said they plan on hiring one such data analyst in 2022.

Analysis was certainly not the only challenge for business leaders and data, however. The collection of the data and implementation of the findings were also rated as very intimidating. And when asked about their top challenges, 44% mentioned how big data is constantly changing. Forty-three percent cited the sheer volume of data as a challenge, while another 40% mentioned the inaccuracies present in the data. Perhaps these many headaches are what have encouraged business leaders to consider outsourcing this year.

A Professional Look Forward

The last piece of our study gave respondents a chance, in their own words, to tell us what they thought about the future of big data.

Data professionals were already sensing the increase in their importance. More than half anticipated an increased investment in things like outsourcing data management, data security, and related software.

One 40-year-old data developer insisted that increased spending in these areas is an intelligent decision, stating, “Companies that gather and use data will outperform companies that don’t. It will be a deal breaker.” Another 27-year-old explained, “… data scientists will be in high demand.” Considering how many business professionals are intending to hire one this year, these predictions are likely correct.

Big Data Made Simple

The data from this study ultimately revealed a continued emphasis on big data. Jobs like data analyst and data scientist will only continue to be in higher demand as more business leaders notice both the importance and the headaches big data can present to their companies. Data professionals echoed the headaches of the role and also understood how big of an impact data analysis can have on a company.

Although most businesses expect to spend more on data this year, all budgets and business sizes can benefit greatly from intelligently understanding their own data. By working with a company like Unsupervised, you can quickly glean insight into why your key KPIs are failing or succeeding, surfacing hidden growth opportunities. Unsupervised uses AI to automate analytics and reveal super specific insights without overwhelming dashboards or wordy reports. To lean on the data expertise of Unsupervised, schedule a time to speak with us today.

Methodology and Limitations

We collected 226 responses of business leaders with big data experience and 233 responses of data professionals in the United States from Prolific. Of our business leaders, 55.6% of our participants identified as men, 43.6% identified as women, and 0.8% identified as nonbinary or nonconforming. Of our data professionals, 53.6% of our participants identified as men, 44.6% identified as women, and roughly 1.7% identified as nonbinary or nonconforming. Participants ranged in age from 18 to 69 years old. To qualify, we used Prolific and prescreened employees and business leaders who were employed at jobs with big data strategies, which included data scientists, data engineers, data analysts, data developers, and other relevant positions. Those who failed an attention-check question were disqualified.

The data we are presenting rely on self-report. There are many issues with self-reported data. These issues include, but are not limited to, the following: selective memory, telescoping, attribution, and exaggeration.

Fair Use Statement

Big data may seem intimidating, but it becomes easier with a little help from reliable information like this. If you’d like to share this content with your audience, you are more than welcome. Just be sure your purposes are noncommercial and that you link back to this page when doing so.

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