AI has made Data Analysis and KPI Tracking More Convenient

AI can automate data analysis and KPI tracking, increasing speed and efficiency

Gaining accurate data analysis and efficient KPI tracking has been a challenge for every organization. With each passing day, companies are gathering more data, and it has become imperative to track this information for businesses to make informed decisions. Implementing AI in analytics and data tracking has eased the whole procedure. Artificial intelligence has relieved the entire operation by introducing new technologies for efficient and accurate insights.

According to the reports, businesses are currently generating 2.5 quintillion bytes of data, and by 2025 the numbers are expected to reach up to 463 Exabytes. The amount of data available to companies today is enormous, but not every industry can manage to handle such vast amounts of data. A study conducted in 2011 reveals that large-scale industries like retail, manufacturing, healthcare, the public sector, and others have not been able to use their data efficiently and hence have not received satisfactory results.

Even after several technological developments, many companies are still overwhelmed by the vast amounts of data to be analyzed. The key factors responsible for this struggle are:

• Time restraints: Between the working hours, most employees do not have the time to analyze such vast amounts of data. They lose interest quickly and eventually miss certain valuable information.
• Cost: Sometimes, businesses cannot afford large investments to implement expensive data analysis tools or hire a team of data scientists who have the knowledge and the skill to analyze vast amounts of data and produce accurate results.
• Limited talent: With an increase in demand for data analysis, employing talented data scientists has been a challenge. There is an acute shortage in the number of data scientists to meet the demands of the industries.

How do AI and Machine Learning help?

Implementing AI tools has proved incredibly helpful at crunching data and understanding patterns. Machine algorithms can scan several datasets repeatedly at the same time. It promotes agility, productivity, and efficiency in decision-making.

• Extensive analysis of the KPIs:

Humans cannot analyze data day in and day out, it is rigorous and can cause a lot of stress, and hence, companies have shifted their focus to KPIs. This technique is more scalable since KPIs will not miss out on potential anomalies and digital performance opportunities.

• Cost-effective and timesaving:

Analyses of data and KPIs are immensely time-consuming. With so many tasks at hand, it becomes difficult for the analysts to dedicate the entire time and energy to one particular task. Even after employing a team of data scientists and analysts, the problem remains unsolved. AI-automated analysis and KPI screening save time and resources and are also cost-effective.

• Real-time data insights:

Without implementing AI, small fluctuations in KPIs could take weeks and months to be detected, and companies might even execute the faulty strategy which will reflect in the customer experiences. Applying artificial intelligence ensures that the process is completed within minutes with real-time results.