Here is a primer on what GenAI can do besides its well-known creative chatting and image-morphing functionalities

Generative AI (GenAI) can do much more than answering questions or creating images. AI technologies, including GenAI, are expected to improve productivity and automated workloads through its analytics capabilities.

For example, in the healthcare industry, GenAI can empower medical professionals to find ways to improve response times so they can provide more attention to patients during periods of high traffic.

With organizations generating more data than ever before, there are greater opportunities for data analysts to align products and services according to customer trends.

Ramprakash Ramamoorthy, Director of Research, ManageEngine

Here are three ways in which GenAI tools augment data analytics for organizations:

    1. Speed and versatility in processing natural-language queries

    With GenAI tools, users can issue complex queries in a more natural way, and fine-tune the answers received with subsequent prompts. This can range from simple requests like getting last month’s sales report, to complex queries like analyzing company revenue patterns throughout the previous decade. By inputting properly-worded prompts, users can exploit GenAI to generate, retrieve and tweak specific data output to suit a wide range of requirements.

    This quick and timely way of processing huge volumes of information enables organizations to translate real-time data into actionable insights. From there, leaders can take steps to create or modify products and services in a more agile way, tuned to user/customer needs, and identify and streamline processes that may be bogging down operations.

    With GenAI, organizations will not have to rely on traditional batch processing techniques, which often take a long time to collect and store data.

    2. Conversion of data into easily digestible visuals

    GenAI makes it easy for organizations to interpret large volumes of data by turning it into visual formats such as animated tables, charts, and graphs. This is especially beneficial in use cases where employees need the complete data set to obtain an accurate picture of how their organizations are performing.

    Furthermore, GenAI can also be leveraged to fill-in missing data by determining the best visual outputs. Data accuracy is maintained, and users will be empowered to sieve out the most salient insights from the data, compared to previously, where data analysis in static text and tables could lead to users misidentifying trends and wasting resources in the resolution process.

    3. Elimination of human error

    Relying on traditional techniques to process data is not only slow and cumbersome, but could lead to users misinterpreting or misjudging the data. GenAI can be used to automatically processing vast amounts of data, helping users to uncover hidden patterns and anomalies.

    By having GenAI do most of the analytical legwork, employees can focus on planning and modifying their initiatives or programs so they can achieve the desired results.


The right tools for the job

Choosing the right GenAI tools is crucial to allowing organizations to respond quickly to market trends and issues. However, leaders may not know what solution can best meet their needs.

For this reason, organizations need to keep these key factors in mind when selecting GenAI tools:

    • Understand your data needs:This includes the amount of data typically handled, and it should reflect accuracy and how diverse the information is.
    • Know the pain points of your operations and achieving business goals: This includes the amount of data typically handled, and it should reflect accuracy and how diverse the information is.
    • Expect an easy-to-use interface and preferred features:This includes the amount of data typically handled, and it should reflect accuracy and how diverse the information is.
    • Assess your budget before acquiring AI tools: This includes the amount of data typically handled, and it should reflect accuracy and how diverse the information is.

With the right AI tools, data analysts can then revolutionize how they brainstorm ideas to provide better products and services and win the hearts of customers.