Artificial Intelligence (AI) apps like ChatGPT, Groq, Claud, and others are making a big splash in the media and workflows around the world with creators touting promising benefits for organizations. For Data Science hiring leaders, the allure of reducing expenses and headcount through the adoption of these AI tools may be tempting. Similarly, Data Analysts may have concerns about the impact of AI on their career prospects.
While future iterations of AI will certainly continue to advance, this doesn’t necessitate an imminent career change for Data Analysts or professionals in Data Science roles. This is primarily due to the fact that AI and machine learning have long been integral components of the data analysis toolkit, predating these recent upstarts. Moreover, according to the U.S. Bureau of Labor Statistics, Data Science careers are projected to grow by 36% by 2032. This growth is attributed to the irreplaceable human qualities in strategic decision-making, creative problem-solving, and team leadership, areas where even the most advanced AI tools currently fall short.
So as a Data Analyst or the leader of a Data Science team, here’s a primer on what you need to consider when integrating AI into your workflows and career paths.
Key Sections
- What’s the Traditional Role of a Data Analyst?
- How Data Analysts Can Use AI in Their Daily Workflows
- The Need for Data Analysts Will Grow with the Growth of AI
- Why VALiNTRY Should Be Your AI-Powered Data Analyst Recruitment Partner
- Choose VALiNTRY as Your Trusted AI-Powered Data Analyst Recruitment Partner
What’s the Traditional Role of a Data Analyst?
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Today, Data Analysts engage in a wide array of data management and analysis tasks. These encompass acquiring, preparing, cleansing, and modeling data, and then creating reports, dashboards, and customized analyses to support business decision-making. Among these activities, the most significant value lies in identifying the crucial changes or trends affecting the organization and gauging potential impacts.
However, Data Analysts often spend disproportionately less time on interpretation. In fact, only 20% of a Data Analyst’s time is typically spent on actual data analysis, with the remaining 80% focused on more routine, inefficient tasks such as data discovery, cleansing, and modeling.
That’s why AI can be such a valuable tool for Data Analysts.
How Data Analysts Can Use AI in Their Daily Workflows
In Data Science, disregarding AI poses risks.
It’s wiser to view these new tools not as threats to Data Analysts and other Data Scientists, but as catalysts for reshaping the field of Data Science and amplifying the value they offer organizations. AI excels at processing vast data sets, identifying patterns, and presenting findings in accessible formats such as reports and documents. This capability allows human Data Analysts to concentrate on strategic analysis and recommendations.
Other ways AI can help Data Analysts include:
Offloading Routine Tasks
AI’s most common role is to automate administrative tasks (statistical analysis, data preprocessing, etc.) so that Data Analysts can focus on higher-value tasks that require intuition and discernment.
Defining Data Structures
AI is capable of aiding Data Analysts in deciding what for example, what records or fields should in a database and how to layout the needed row and column headings.
Automating Data Discovery
AI excels at exploring infinite permutations of the data it receives and quickly surfacing statistically relevant and meaningful results so that Data Analysts can spend more time focused on interpreting the findings.
Designing Visualization
AI helps Data Analysts with recommendations of what visualizations would best convey the results and how they should be built.
Reducing Errors
AI’s ability to rapidly process data and calculate formulas enables Data Analysts to have more consistent and accurate results.
Forecasting Trends
Data Analysts can use AI-powered predictive analytics to expand their capabilities and deliver valuable recommendations for strategic planning.
Building Personalized Reporting
AI can assist Data Analysts in taking the same data and creating personalized reports for the C Suite, Marketing, Operations, etc. so the results speak directly to the needs of each audience.
Standardizing Training
Data Analysts can use AI to develop standardized training that helps other team members apply AI tools to their own data.
Gathering Relevant Data
Data Analysts can use AI to develop standardized training that helps other team members apply AI tools to their own data.
Gathering Relevant Data
AI can help Data Analysts assemble relevant data sources for a particular project more quickly than Google with a prompt as simple as “Please provide me with six verified data sources on workplace safety in Oregon?”
Creating Datasets for Testing
AI tools can create fabricated but realistic large data sets for a variety of purposes, such as Data Science research projects or training other AI models. permits connections to multiple data sources and facilitates the creation of interactive dashboards and visualizations.
Microsoft Power BI
Microsoft’s competitor to Tableau provides users with data automations, predictive analytics, and interactive visuals.
Polymer
A simpler tool than Tableau or Power BI, Polymer offers an AI-powered solution for small businesses
These tools not only enhance accessibility to data analysis but also enable users to interpret, visualize, and utilize data. As AI technology progresses, it is realistic to anticipate further improvements in the ability of AI and Data Analysts to derive more actionable and valuable insights from data.
The Need for Data Analysts Will Grow with the Growth of AI
The importance of Data Analysts will continue to rise alongside the expansion of AI.
Despite advancements in AI, it cannot replicate the essential human qualities crucial for critical thinking, strategic planning, emotional intelligence, and ethical judgment. As organizations increasingly incorporate AI into their operations, the significance of these skills will only grow.
Data analysts must evolve into and be regarded as genuine business partners, leveraging their data literacy to interpret information, provide context to insights, and develop data-driven solutions.
As hiring managers, it is imperative to continually invest in Data Analysts proficient in confidently and securely utilizing artificial intelligence tools.
Why VALiNTRY Should Be Your AI-Powered Data Analyst Recruitment Partner
When it comes to hiring AI-savvy Data Analysts and other IT talent, VALiNTRY stands out as a trusted partner with over a decade of experience in IT recruitment. But beyond simple experience, there are several reasons why VALiNTRY is your preferred IT and Data Analyst recruiting partner:
AI-Powered Recruiting Experts: VALiNTRY has been on the bleeding edge of AI-powered recruiting since 2015 thanks to our proprietary and award-winning V-FiTT technology. We know how AI works in business and recruiting because we built V-FiTT from the ground up and still continue to use and improve it today.
Choose VALiNTRY as Your Trusted AI-Powered Data Analyst Recruitment Partner
With VALiNTRY’s expertise in AI-powered Data Analyst Staff Augmentation, you will be able to streamline your hiring process, reduce costs, and secure top IT and Data Analyst talent FAST.
Put VALiNTRY’s 10+ years in the Data Analyst Staff Augmentation business to work for you.
Contact us today to discover how VALiNTRY can become your preferred IT and Data Analyst Staff Augmentation Agency!