5 Major Challenges Faced By The Companies While Doing Their Data Analytics

With the growing competition, it is imperative for businesses to work towards securing their future growth. For this, they have turned towards the realm of data analytics that looks promising. However, there are many challenges that these companies are facing in terms of process synchronization, people and skills to harness the power of analytics. 

Therefore, these are some data analytics challenges that business analytic courses teach to prepare aspirants to cater to the business requirements accordingly.

1. Understanding how data management fits the business: There is no set rule for applying data analytics to the business. Each business has different requirements and depending on those requirements, new business models are being created to analyse vast data stored with the companies. Some companies prefer flexibility and others vouch for more functionality. Therefore, businesses need to be careful while applying any approach and use it only to the limit of its relevance in a particular business setting. Otherwise, it may end up as a waste of time and effort.

2. The talent gap: Another big challenge that companies are facing is that the number of people technically skilled in data analytics is much less than the positions being rolled out. Technologies are being innovated faster than the number of people being trained which results in a skill gap. And this gap is responsible for not being able to harness the true potential of the application of data analytics in businesses to flourish. Where companies require experts in data and modelling and architecture, people’s experience tends to lie in programming, tools and platforms.

3. Getting organizations on board: The success of business analytics lies in the company-wide understanding of this whole subject. It means that not just the team with a diploma in business analytics but the employees at other levels too must understand the importance of big data and capturing relevant information.

4. Join up data sources: After integrating data in the big platform, it needs to be in sync with other information. Lack of this required synchronization of data can lead to wrong analysis and application of such analysis can result in total disaster for any company or business. Making decisions on bad insights can prove to be more damaging than not having any data at all.

5. Extracting the relevant insights: In the present scenario, we have a huge volume of raw data at our disposal. But to process that raw data to extract relevant business information for its growth is more difficult and requires skilled analysts. If this raw data remains in the storage unused for an extended time, it poses a greater challenge. Because then it becomes more difficult to process it accurately and draw valuable insights from it.

We can conclude the article by saying that to harness the true potential of the big data available with the enterprises, more people need to be trained in business analytics courses and must be given rich experience in the same. This will help them both understand and tackle the challenges of data analytics and extract valuable information from it.