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The Future of Business Intelligence: How Big Data Analytics Drives Success with Real-Time Insights
The Future of Business Intelligence: How Big Data Analytics Drives Success with Real-Time Insights

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The amount of online data has become so massive that it’s no longer data anymore. Rather it has been given a new name: Big Data. The ‘big’ in big data stands for its sheer volume and complexity.

“If you want an idea of the amount of data that is being generated in just a single day, then here’s a startling statistic: Every day, we produce about 2.5 quintillion bytes of data. That’s 18 zeros after 2.5!”

Although analysing big data alone can be valuable, integrating low-density big data with structured data can provide even greater business insights. By capturing various forms of big data, such as customer, product, equipment, or environmental data, and by adding relevant data points to your core master and analytical summaries, one can draw better conclusions.

For instance, analysing customer sentiment, as opposed to just top customers, can lead to different conclusions. Therefore, many view big data as an essential expansion of their existing business intelligence capabilities, data warehousing platform, and information architecture.

It’s important to note that both human- and machine-based big data analytical processes and models exist. Big data analytical capabilities encompass a range of techniques such as statistics, spatial analysis, semantics, interactive discovery, and visualisation. By utilising analytical models, you can identify correlations among different data types and sources, leading to significant findings.

For organisations across various sectors to get the most out of their data, they need to leverage advanced analytics techniques. This is where big data analytics comes in. Analytics, as the term suggests, is the process of analysing data to gain insights and intelligence.

Why is Big Data & Analytics Important?

Big data and analytics are intertwined. Big data is the raw material that needs to be processed and refined to gain insights. Analytics, on the other hand, are techniques used to extract insights from raw data.

So, why is big data and analytics important?

Big data and analytics can help organisations gain a better understanding of their customer base, devise marketing strategies, identify new opportunities for growth & innovation, and make better decisions.

Solutions for Big Data & Analytics

With the right solutions, organisations can make sense of their data and use it to their advantage. One such solution is advanced analytics. Advanced analytics uses sophisticated techniques such as machine learning, predictive analytics, and deep learning to extract insights from large amounts of data.

Benefits of Using Big Data & Analytics

The advantages of drawing insights from Big Data Analysis are numerous. While each organisation has its own benefits, here are some common ones:

 Improve Organisational Wide Data Breadth

Big Data Analysis helps improve Organisation-wide data breadth by tapping into content sources that are not readily apparent.

 Improved decision-making

With the help of advanced analytics, Organisations can make better decisions based on data-driven insights.

 Better customer understanding

Organisations can gain a better understanding of their potential and current customers by analysing the data generated by their activities. This helps them devise better marketing strategies to target the right customers.

 Enhanced operational efficiency

By leveraging analytics, organisations can identify inefficiencies in their operations and take corrective action to improve efficiency. This, in turn, can help them save costs and maximise profits.

Conclusion

Big data & analytics are essential components of success in the digital age. Organisations that leverage sophisticated analytics tools and techniques can gain valuable insights from their data and use them to make better decisions and create value for their customers. With the right approach, Organisations can leverage big data & analytics to gain a competitive advantage.

About the Author:  Nikhil Kumar, is having over a decade of experience, and heading MOTIF (Motherson Intelligence Framework),  Analytics Solutions Suite in Motherson Technology Services.

 

 

 


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