How Your Data Problems Are Killing Your Business? Learn How You Can Fix Them

January 10, 2022

So, you decided to reform your business by following the data route. To introduce future-centric growth, you brought in every buzzword-related product such as agile development, dev-ops, and so on. But somehow, instead of showing growth, data is killing your business. The problem? Your data management!

Data or Big Data is the latest buzzword penetrating the business market today. With more and more users connecting online, the opportunities are spurring the scalability of the businesses. 

However, collating databases is not the endgame to solve the businesses face today. You will require a more inclusive and innovative approach!

What are the Roadblocks Businesses are Facing with Data?

Technology is a powerful intoxicant. It lures you in with the most promising future without giving you a map to reach there. The businesses are faltering on finding their routes to growth and success. 

Using the trendiest of tools and technology will not drive the results for your business. Unless, of course, you know what you want and can navigate around the pitfalls the approach delivers!

Poor Data Quality

The most consistent data set wins the race. The universal rule for data management is its applicability in the decision-making process. However, the businesses have failed to realize the importance of a consolidated, consistent database. 

The more inconsistency your data set will have, the higher are the chances of error. With variables compounding in every collection, wrong decisions increase manifold. 

Solution: Constant data access with a unified database helps your analytics and supports long-term predictive success. Collect, integrate and transform your data in layers before it reaches the analytics stage!

Cultural Shift

Data has brought the evolving and efficient mechanism into the domains of businesses. Even with the most pragmatic approaches, failure is inevitable due to the lack of will to drive dynamism in the execution. 

According to Harvard Business Review, only 1/3rd of the businesses that initiate data-driven insights end up adopting it. The companies are focusing on the execution more than the mindset behind it. 

Solution: With cultures making a drastic shift from knowing to learning, the flexibility in execution is now more than necessary! To bring in a cohesive and sustainable approach of objective decision-making against the command-based is the need. 

Steering the Skills Ship

As much as data lies at an organization’s core, the talent to read and analyze it is underwhelmingly low. The surge in the application of data analytics hasn’t given ample time to the opportunity takers to hone themselves, leading to the shortage. 

Solution: You can have the dart and the arrow, but you cannot win without the expert hand to hit the bull’s eye. Your business won’t reap the benefits of data science if the analytical hand is missing. Your organization needs the R-U-T (Reskilling, Upskilling, and Training) of talent management!

Misalignment with The Vision and The Goal

With one leg in the boat of the past and another on the future land, the businesses forget the present state of affairs. In a rush to adopt data analytics, the companies’ vision concerning their objective has become foggy. 

Solution: Data always suggest a future decision based on the insights it has created through patterns. It is always suggestive and not absolute. The business solution data will deliver depending on the goal you have undertaken. Keeping in mind the company’s objective helps with marking the exact problem.

In Summary

Today, even with the silos of data lying with your cloud services and a goal to hit, the companies stumble. Reaping the benefits of data for your business has more to do with adopting complementary but essential practices. Data management isn’t merely a subscription of the consultation services and tools but practice for your entire organization. 

Are you ready to bring the revolution that data science is excited to bring to you?

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