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Will Big Data be able to beat the upcoming recession?
Will Big Data be able to beat the upcoming recession?

December 2, 2022

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As a result of impending doom in the market, businesses are making rash, impulsive decisions. New projects are halted, expenses are reduced too low, and employees are brutally laid off. Business leaders are concerned about the unpredictable nature of future events while trying to navigate through a possible recession. Some of this stress can be relieved by data. During economic downturns, it is the single most valuable asset an organization has.

In the coming months, it will be crucial for enterprises to find ways to conduct business while significantly cutting down costs. Data will provide them with the comfort and familiarity they need to make such informed decisions. Organizations can find tasks that can be automated or point out ways to enhance their efficiency by using advanced data analytics solutions. Utilizing BI technologies can assist in identifying customer involvement, accounts that have been spoken to, and accounts that need attention. Regardless of the state of the global economy, data analytics may help organizations identify and forecast the parts of their business that are most likely to succeed. 

However, raw data does not provide business insights, so effective and efficient data lifecycle management is necessary to transform it into valuable business insights.

During the looming recession, how can data help companies stay afloat?

Businesses can make better decisions based on accurate and reliable data analytics rather than guesswork and assumptions. Here’s how: 

  • Minimizing risks: It is crucial for companies and organizations to assess their past data to identify inefficiencies, redundancies, and oversights to reduce risk. Enterprises are then able to make data-driven judgments and steer clear of expensive errors that won’t benefit them in the long run.
  • Observing consumer behaviour: It’s crucial to both analyze and study consumer behaviour on an ongoing basis, especially when you have economic doom ahead of you. Data must be structured, categorized, and studied in order to understand the changes in consumer behavior, buying behavior, preferences, etc, before, during, and after a recession.
  • Operational efficiency and productivity: Granular-level insights into operating procedures can help enterprises accurately determine areas that require improvement and thus concentrate their efforts to rejuvenate it. It can also help them analyze time and effort ratios to assess manpower utilization and take necessary steps that help meet business and market demands. Many times, data trends can indicate low-performing areas with low ROIs that can be paused or discontinued.

To achieve the above, enterprises must first tackle the task of organizing unstructured data that is generated every day in order to use data to its fullest potential. Without efficient data management, businesses may experience data silos, inconsistent data sets, and poor data quality, all of which may limit their use of business intelligence (BI) and analytics applications and even result in incorrect conclusions. In order to maximize data utilization, lower storage costs, and uphold security rules, unstructured data must be structured.

 

 


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