Data analytics challenges companies face in 2021

Data analytics challenges companies face in 2021

Intelligence solutions

Regardless of what a company does, there is no doubt that it needs to make the right decisions in order to survive in the corporate world. Decision Intelligence is essentially a composite domain containing artificial intelligence and data science as well as decision making and management science concepts. In simple terms, this means that decision-makers such as corporate executives, shareholders, etc. They can use machine learning algorithms to get information from their data and make the best decisions using that data. Decision Intelligence is growing in popularity because of the benefits it provides to companies and currently accounts for about 33% of companies using this technology across all sectors. (If this is a company you’ve heard of, chances are they are using Intelligence Intelligence!).

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Data history

Now data stories are becoming more and more popular. Would you rather just see facts and figures about data organized in a dashboard, or see a story that shows the data path for your company? Most of you will pick a good story any day! This is why data stories are becoming so popular, especially for non-professionals with no specific knowledge of data analytics consultancy . Gartner even predicts that by 2025, data stories will become the most popular method for communicating analytic data. So if you’re a good storyteller and a good data analyst, you’re in luck!

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Changes in six months

In June 2020, Gartner published “Top 10 Trends in Data Processing and Analytics Technologies for 2020”, and in March 2021 – “Top 10 Trends in the Development of Data Processing and Analytics Technologies for 2021”. The first document was supposed to help companies respond to the changes brought about by the coronavirus and prepare for a post-pandemic “reset”. The second is also to help them seize the opportunities that are opening up in 2021.
The name of the first trend literally coincides – “Smarter, faster and more responsible AI”. But the content is different, if in 2020 it was mainly about creating “smarter and faster” artificial intelligence, then in 2021 not only the need for “ethical responsibility” of AI is mentioned, but also less demanding data.
In another trend, Gartner reverts to this idea, pointing out that the dramatic changes in business due to the COVID-19 pandemic have made machine learning and artificial intelligence models based on large amounts of historical data less relevant. Therefore, it is necessary to reduce the dependence of AI models on data volumes, to learn how to achieve the effect of using small data sets of various nature, to achieve synergy from their use.
However, this is not the only factor that needs to be taken into account. What else will need to be entered into the system:

  • The average number of incoming calls on each of the days of the week, months, seasons (in summer, for example, they will be less due to the time of holidays).
  • Distribution of calls throughout the day.
  • The number of operators, their vacation schedule, set by law 2 days off per week.

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