BIG DATA ANALYTICS – the next big thing that’s already here.

Last week, Alan told me he’s a professional systems analyst. I did not know that. He’s as serial as a serial entrepreneur can get. Now suddenly it all means sense; his insistence on us gravitating towards massive data-generating activities; his reiteration that we value higher traffic than higher margins; and lastly, it explains that “the data is everyfin” mantra he’s drummed into my head for years with his 75% British accent.

So when I caught up with my old buddy Esi a couple weeks ago and she repeated similar lines of thought, we had a fun conversation on where Ghana is headed and can head when local companies and organizations catch up to the Western World’s effective utilization of Big Data and Predictive Analytics. She has a Master of Science Degree in Information Systems with a concentration on Big Data Management and Analytics… and she’s kind of a walking encyclopedia on big data because she really is that good!

Nana Esi Afedzi hadn’t been to Ghana since leaving for the States 13 years ago, roughly the same amount of time I’ve known her. You can bet she enjoyed her Year Of Return! The Taadi girl now works at ACCENTURE, one of the world’s largest consulting firms and a Fortune 500 company, as a Big Data Engineer with a strong background in Data Analysis, Data management, Solution Architecture and Data Visualization.

At ACCENTURE, she’s part of the team that developed a Finance Analytic Tool to be used by Walmart’s CFO to visualize different financial reports that are generated to display profits, losses and overall finances. She also designed a plan using Azure Cloud services to copy many years of transaction logs from servers to Azure cloud storage. I could type many more.

Here’s her take on Big Data Analytics, it’s impact on the finance sector and how other companies can utilize it for profit maximization.

The following is authored by Nana Esi Afedzi.

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We live in a world of technology. Various technologies behind the scenes allow you to seamlessly perform your different daily routines. From checking your bank account balance or mobile money on your cell phones, to logging in to YouTube and seeing a video you are actually interested in recommended on your homepage, Big Data Analytics is used to make these seemingly minor things happen effortlessly. So, let’s pull back the curtain on Big Data as we ask ourselves just one question:

What is Big Data, and why is it labeled “the next big thing”?

Big Data is considered Big Data because of Volume, Veracity, Velocity and Value. A good example of data that qualifies as “Big Data” is the data from Transaction Logs. This data is a record of all transactions made by customer in a given period, be it five years, ten years or even twenty years. Imagine the amount of data you’d have after decades of keeping records of what each customer who came to your grocery store purchases.

If you think about the volume of data that is collected, you might start wondering where all that data is stored. This is where cloud storage comes into play. Cloud storage and Big Data go hand in hand. It allows for efficient storage, faster processing times and the ability to retrieve real time information in a rapidly fast amount of time.

Use of Big Data Analytics for profit maximization in companies

Companies venture into businesses to increase the capital they initially invested in their startup. The utilization of Big Data Analytics is essential in ensuring maximum profitability.

Think about Facebook, for instance. Many data scientists refer to Facebook as a “Data Wonderland”. I mean, Facebook has over 2.4 billion monthly active users. The main aim and business strategy at Facebook is to get more insight into their users, understand their activities, and be able to use that to accurately advertise to them. This can all be achieved through the massive data and the analytics that they collect.

A report from McKinsey and Co shows that every sixty seconds, 136,000 photos are uploaded, 510,000 comments are typed, and 293,000 status updates are posted. That’s a very considerable amount of processed data for just every sixty seconds! The use of Hadoop and other big data tools and software gives Facebook the means of understanding both the users and their market for advertisers. Data analytics allows businesses to use person-centric analytics in helping them understand the market in a much better way. Because of this, Facebook, for instance, is effectively able to cluster users and offer them ads in a more insightful way.

Aside this example, Big Data Analytics help other businesses to maximize their profits by reducing the expenditure incurred. Data collected regarding the business can be used in the identification and elimination of business inefficiencies systematically. This leads to an improvement in business efficiency and overall corporate efficacy. As such, it is attributed to the reduction in business expenditure. These measures lead to the growth of generated revenues.

Big Data Analytics also helps in the profits of a business by engaging in profitable compliance. Non-compliance has been attributed to large fines, which have led to the failure of many companies. As such, the use of Big Data Analytics enables businesses to ensure that their processes meet the compliant as stipulated by the regulations in place.

This can be done by using low-cost methods that are honest and meet the required compliance. Firms can facilitate this better when they have the corresponding data regarding their compliance programs. For example, companies should ensure that data analytics is essential in the auditing and compliance programs of their businesses.

Big data analytics can also increase the profits of an enterprise through a massive increase in business valuation. A higher valuation can be obtained by emphasizing the economic value of an industry. Value creation can be done through the establishment of person-centric data practices.

Use of Big Data Analytics in the financial industry

Due to advancements in technology, the financial sector, in its quest to increase efficiency and improve on their profitability, often use Big Data Analytics visualization tools like Tableau. Most financial institutions that I know are bestowed with the task of calculating customer credit scores that assist them to issue premiums and approve loans. This requires factoring in as much data as possible.

For some companies, some of this data is generated from the device they might ask you to install in your car to track your driving habits for reduced car insurance rates, linking your social media habits with your savings activities to better understand your savings and investment habits, and using location tracking services to determine when a fraudulent purchase is being made with your account.

Big Data Analytics is also used for customer segmentation in financial institutions. Due to increasing competition between financial institutions, the financial industry is shifting from business to customer-centric models. The shift can only be enhanced through the performance of customer segmentation.

Customer segmentation helps in providing better financial solutions to clients. Big Data Analytics is used in customer segmentation based on historical and real-time data. This hastens the overall customer segmentation process.

Big Data Analytics is also used in blockchain technology. The rising case of cybercrime in the financial industry has led to the adoption of blockchain technology and data compliance measures. Blockchain technology applies the use of big data since its data is stored in ledgers. After that, the ledgers are distributed and saved on the financial institution’s servers, which makes it secure from hackers.

Big Data Analytics really helps financial institutions to improve their data processing and storage. It uses algorithms and codes which help for continuous processing of large volumes of data which had been saved by banks for an extended period.

Impact of Big Data Analytics on the world of finance

Big Data Analytics has led to numerous effects in the financial industry. FinTech companies are handling this by using big data to offer unparalleled levels of convenience. They're taking away a sizable chunk of traditional financial firms' revenue by eliminating friction for customers.

For example, payment companies such as PayPal and CashApp now allow customers to easily make payments online or participate in peer-to-peer lending.

By contrast, traditional financial firms lack the infrastructure to support those types of services and are unable to understand how customers are using specific applications. They rely on things like surveys rather than real-time data to discover how customers are responding to their services.

TransUnion, one of the top three credit bureaus, provides credit information, information management services and analytics to roughly 45,000 businesses and 500 million consumers worldwide. When they realized that their legacy platforms would be incapable of achieving the company's goals of digital transformation and enhanced innovation, TransUnion looked to modernize its data platform in order to provide its analysts and data scientists with greater flexibility in accessing all data and discovering insights.

The success of this self-service intelligence encouraged TransUnion to create a new line of business: to offer market insights directly to their customers and improve customer engagement. By doing so, they enabled their customers to make smarter decisions and develop improved risk strategies. One example was how large banks could see the curve of delinquency rates based on the origination of loans and acquisition rates over time. They could also do a peer analysis to see their delinquency rates versus their peers.

The technology has helped the banks in improving their predictive power regarding risk models, improve system response, and develop risk management methods. Following this, financial institutions can now better manage market and commercial loans, fraud, credit, and operational risks.

Conclusion
Big Data Analytics has served an integral function in the evolution of the development of enterprise. The use of this technology has led to an increase in revenue and, subsequently, the profitability margin of different businesses. Data drives the business environment in the 21^st century. As such, data analytics is essential in making concrete decisions regarding many businesses.

It allows for the decisions involving actions of a business in both short and long-term durations. The tools used can help companies improve on operations, reduce costs incurred, and maximize profits.

The emergence and subsequent utilization of Big Data Analytics across many institutions has been nothing short of a phenomenal occurrence and it has materially contributed to revolutionizing the world of business and industry as a whole.

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Hit me up on social media and let’s keep the conversation going! I read all the feedback you send me on LinkedIn, Twitter, Instagram and Facebook.

Also, feel free to send me your articles on relevant topics for publication on the Macroeconomic Bulletin. I’d give you full credit, an intro, and an outro. Kindly make it about 1000 words.

Have a lovely week!
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Maxwell Ampong is the CEO of Maxwell Investments Group, a Trading and Business Solutions provider. He is also the Business Advisor for the General Agricultural Workers’ Union of TUC (Gh). He writes about trending and relevant economic topics, and general perspective pieces.