Embracing Big Data Could Increase Profitability Margins by 60%

Introduction 

With the rise in the amount and variety of data – in both structured and unstructured formats – the concern on how to manage data in such a way that it provides better storage, greater insights, and increased productivity to grow the business. Data sets such as these would be impossible to process manually, which is why so many databases and tools have emerged.

Big Data statistics from across the globe indicate that data is the key to transforming any business. However, there are still a lot of companies out there not investing properly in analytics solutions. Though we’re constantly creating and discovering information, we’re not always leveraging it correctly. That could be about to change.

73% of data goes unused for analytics purposes

Through big data analytics, modern businesses can forecast market fluctuations, discover more lucrative business opportunities, improve their efficiencies, beat their competitors, and provide a more customer-centric service and experience. Big data and all of its technologies are the keys to unlocking the abundant potential of the online world. But the main question that arises is are you using your data at its full potential?

Forrester’s report suggests that between 60 and 73% of all data is never used for analytical purposes. Despite more companies talking about big data today, many brands simply don’t have the technology available to access the right data insights. ( “Hadoop Is Data’s Darling For A Reason.” Forrester. (https://www.forrester.com/blogs/hadoop-is-datas-darling-for-a-reason/).

Are you utilizing your data properly?  

When it comes to the pros and cons of big data, much of the buzz about IT in recent years has to do with the use of big data in business and how big data benefits help businesses to simplify their operations, improve efficiency, and reduce costs. , and a host of other great things. But as with other forms of technology and all aspects of life, with huge data, advantages and disadvantages go hand in hand.

The main purpose of storing, processing, and analyzing big data is to examine large data sets to identify trends, patterns, and details that can be used for a variety of purposes. The major advantages and disadvantages of data are primarily derived from the ease of doing this and the value or shortcomings produced by these processes in the end.

Proper use of big data offers several advantages like

Opportunities to Make Better Decisions: 

When a lot of information is available in a form that organizations can easily manage and analyze, they are more likely to discover patterns and insights that can inform operational and strategic decisions. Data-driven insights provide a foundation for making more informed and reliable decisions.

A study by BARC indicates multiple benefits of using a big data initiative, including better strategic decision making (69%), improved control of operational processes (54%), and improved understanding of customers (52%).

Improved customer service:

Technical support and helpline services powered by Big Data, Machine Learning (ML), and Artificial Intelligence (AI) can significantly improve the standard of response and follow-up that organizations can deliver to their consumers. Responsible use and analysis of customer and transaction data enable organizations to personalize their access to individual consumers, leading to greater engagement with brands and the more satisfying user or buyer experiences.

Big data generate big results. McKinsey reports demonstrate that data-driven organizations with insights into customers are 23 times more likely to collect new clients. They’re also 6 times more likely to maintain the customers they gain.

Increased revenue and reduced cost

Sorting operations, improving efficiency, and increasing productivity using big data can save the company significant costs and have a positive impact on overall profitability. Using large data in predictive or prescriptive analytics processes driven by machine learning and artificial intelligence can further reduce costs. This can be through identifying more efficient ways to do things or through mechanisms such as preventive management and advanced quality control management.

McKinsey’s studies on Big Data as the next frontier for innovation and competition found that businesses embracing big data analytics could increase operating margins by up to 60%. 

Some of the disadvantages of big data include

Questionable Data Quality

Data-driven decisions and operational strategies can only be as good as the quality of the underlying data sets and their resulting analysis. There’s a danger that the insights gleaned from the analytics of such data might be worthless. In extreme cases, proceeding with the insights and assumptions produced may even prove to be harmful.

Forrester reports suggesting that between 60 and 73% of all data is never used for analytical purposes. Despite more companies talking about big data today, many brands simply don’t have the technology available to access the right data insights.

Cost and Infrastructure Issues

Maintaining an on-premises infrastructure for big data management can be a complex and capital-intensive affair. Distributed storage and analytics hardware and infrastructure may be too expensive to purchase, manage, and maintain. Cloud-based analytics and big data management solutions offset this to some extent, but there are deployment and governance issues that enterprises must address even here.

Big Data Skills Shortage

To take full advantage of big data, companies need data scientists and other big data professionals who can design, implement and manage results from infrastructure and analysis. Although there is currently a severe shortage of skills in these areas and talent is available, salaries for big data professionals can be very high for the enterprise budget.

According to reports, the benefits of big data are clear to many companies, yet around 63% of employees say they can’t get insights from their solutions in the right timeframe. The biggest problem for many companies may be collecting data insights before they’re outdated.

Recommendation 

Data lake- data management solutions that can help business users meet big data challenges and drive new levels of real-time analytics. Their highly-scalable environment supports extremely large amounts of data.

A data lake can meet such big data challenges and can give a highly scalable environment to support huge data volumes coming from a variety of data sources in their native form. Data lake enables an organization to manage, explore and access large data sets. It provides a base for Machine learning and analytics and provides a framework for the data warehouse.
learn more about the advantages of the cloud Data Lake

Conclusion 

As the volume and resources of data continue to grow, more and more businesses are learning how to turn their vast amounts of information into valuable business assets. The goal of collecting and analyzing big data is to increase the speed of products coming into the market, reduce the number of resources required to adapt to the market and optimize customer experiences. Businesses that harness the power of their data lake will position themselves to grow more efficiently with a competitive advantage and could experience increases in profitability margins by 60%.