Big Data — Is It Asset or Liability?

· One jet engine can generate more than ten terabytes of data for only 30 mins of flying

· The NYSE generates more than one terabyte of new trade data per day

· Photo, video uploads, messages, and comments on Facebook, Instagram, or on YouTube create more than 1000 terabytes of new data every day

Wow? A lot of Data, right? So that’s what we call Big Data.

What is Big Data in Finance?

Big data in finance is the key to providing critical decision-making insights. However, unstructured data exists, and it deals with substantial diagnostic prospects.

Analysts monitor the billion-dollar data movement daily with precision, security, and speed to establish predictions, uncover patterns, and create predictive strategies. Cloud-based big data solutions cut costs of on-premises hardware with limited shelf life and significantly improve scalability, dimensional flexibility to integrate security across all business applications, and, most importantly, garner a more practical approach to big data analytics and predictions.

Organizations have a unique opportunity to start analyzing their data (I call it “organizations’ digital asset”), which will make informed decisions on uses like improved customer service, fraud prevention, better customer targeting, top channel performance, and risk exposure assessment

It came up to five main challenges when it comes to big data and business intelligence:

How does it work?

It is a fact that the more we know about anything, the more we can gain insights and decide or find a solution. Of course, this process is completely automated in most cases — having forward-thinking software and tools that run 100 million simulations to provide us the best possible outcome. However, achieving that with the help of machine learning, Robotic Process Automation (RPAs), or even artificial intelligence (AI), we need to know how Big Data works and set up everything strategically and correctly.

We are in a position when managing so much data requires a stable and well-structured infrastructure. In addition, it will need to process huge volumes and different types of data quickly, which can overload a single server or cluster.

Understand the Six V’s of Big Data

Volume — this represents the volume, amount of data growing at a high rate, what about- data and information volume in measurable units.

Velocity — the measurable rate at which Data grows. Today’s social media plays a significant role in the acceleration of increasing data.

Variety — it refers to the different data types and formats like text, audio, video scripts, images, etc.

Variability — it defines the need to get meaningful data considering all possible circumstances.

Veracity — this raises the improbability of accessible data. It usually arises due to the high volume of big data that brings incompleteness and changeability.

Value — this refers to turning data into value. By turning accessed big data into values, businesses may generate revenue.

How do we adopt Big Data in finance?

The digital transformation is fostering the data-driven culture to enable better-informed decision-making. The significance of optimal decisions needs no explanation as they are paramount to determine the business success rate, respond to the present and future challenges, and gain a strategic advantage over the competitors. Such decisions can be taken only based on the data facts, not on the gut instincts. However, it lingers a question: how big data or insights can be translated into crucial business decisions. The disconnect between extensive data and the managers that implement the decision can be bridged through analytics. The big data analytics technology leads to quick, accurate, and knowledge-driven decisions by uncovering the hidden insights from the data that help the businesses act and make the most out of the opportunities.

Most big companies strategized on significant data adoption and proved that big data solutions are accurate. But, of course, each financial company is at its level of extensive data application and maturity. Still, the critical question is, “How can big data provide resolution of our major corporate and organizational issues?”

Whether the core issue is customer experience, operational optimization, or improved business processes, organizations must timely and intelligently clasp the data-driven transformation that big data and cloud-based solutions promise.

1. Define a data strategy. A comprehensive approach will span all aspects of individual departments, crossing the network of partners. In addition, companies must underline strategies to focus on long-term solutions instead of bandaging short-term falls.

2. Select the right platform. The needs of each business are different. Selecting a cloud data platform that is phenomenally flexible and significantly scalable will allow companies to collect essential data as necessary while processing it dynamically in real-time. Tracking Data granularity and ensuring that valuable information is accessible to key players will make or break a data strategy.

3. Offer the opportunities. Identifying the entire ecosystem of the data queue, undertaking one business challenge at a time, and expanding from one unique solution to another makes the application of big data technology cohesive and realistic. As a result, primary use cases can quickly be built upon and developed over time.

Where is Big Data headed in the future?

Big Data is a game-changer in many fields and will undoubtedly continue to grow. Just imagine how much this can change our lives in the future! Once everything around us starts using the Internet (Internet of Things), the possibilities of using Big Data will be enormous. The amount of data available to us will only increase, and analytics technology will become more advanced.

The digital era of disruption is here. Our mission is to make the business agile and responsive to the digital economy is the only way to survive, progress, and get ahead of the pack. The decision-making process plays a vital role in deciding the present and the future of the businesses because the businesses won’t run on intuition.

Takeaway: Big data analytics is revolutionizing businesses through instant data-driven decisions as real-time insights and predictive analysis make businesses and organizations proactive and alert to any change in the niche industry.

My cent: Embrace big data analytics to not miss a single opportunity with the right decision!

Author: Ketevan (Kate) Koraia, MBA, FinTech Professional

9.25.21