What is Big Data Analytics and Why is it so Essential?
If you are thinking of ….
Collecting and Processing large data sets and also wanted to analyze and find the hidden trends, important correlations, and other deep insights than you are thinking of Big Data Analytics.
Do you know … The vast amount of stored data is valuable information in raw format. By inspecting, cleaning, transforming, and modeling the data, companies find useful information that leads them to accurate decision-making and meaningful actions.
“It is the way to examine large amounts of data to uncover hidden patterns, connections, and valuable insights.”
Now using the latest technology, it is possible to analyze data and find the answer to what you are looking for.
In this article, we will understand the definition of big data analytics and why it matters.
First, Let’s Understand Big Data
The term “Big Data” can mean various things to different businesses of today. Depending on the business size, role and the reason behind obtaining the data determines the definition of big data for many organizations.
In layman’s terms, big data can be defined as the structured and unstructured data moving throughout the organization.
The structured internal data includes processed transactions, customer insights, payable information, and receivables.
While the unstructured data includes emails, photo images, customer reviews, and social media posts.
In conclusion, the data is extracted from ATMs, sensors, smartphones, web clicks, GPS signals, and many more to name a few.
Big data in simple words are massive amounts of stored data that can be analyzed for business profit.
Companies keep a track of their customers and all this structured data is stored in the form of spreadsheets or tables.
This can be carefully examined to understand the behavior of customers.
Using data through business analytics can lead to smart decision-making, optimize business outcomes & offer ‘personalized offer’ to customers.
What is Big Data Analytics?
Big Data Analytics involves
- Extracting data from different sources
- Cleaning & Transforming it in a way that it becomes available to be consumed by analysts
- Doing an analysis of this data to derive insights, which are useful to the organization’s business.
The process of converting large amounts of unstructured raw data, retrieved from different sources to a data product useful for organizations forms the core of Big Data Analytics.
The process and tools required to extract insights from massive amounts of data are part of big data analytics. The data is often defined by the 3Vs – Velocity (high), Volume (large), or Variety (extreme).
Big data analytics works efficiently to derive conclusions and correlations from the large chunks of unused data. It’s done with the help of tools such as python, Hadoop, R, and others.
Why is Big Data Analytics Essential?
The importance of big data analytics is becoming more apparent among various industries.
Big data analytics helps businesses to extract value from their data and create new opportunities.
This leads to better decision-making for the business, efficient operations, higher revenue, and satisfied customers.
Big corporations and enterprises utilize big data analytics to provide an excellent customer experience.
Big data helps businesses to use their data efficiently and create new profitable opportunities.
The data can predict the potential success of products among customers based on their interaction by using different techniques and algorithms.
Here are 2 major reasons why big data analytics matter
Enhanced Decision-Making – Teamed with great speed of Hadoop and in-memory analytics and the ability to analyze new data, organizations can examine information quite rapidly and make better decisions from the collected insights of the customer behavior.
New Products and Services – Analyzing collected data can help immensely with predicting the success rate of new products and services. It also helps companies to create products and services based on analytics of customer preference.
Now companies can really understand each of their customer & offer ‘personalized solution’ to the customer, in his context. No, one size fits all or even, segmentation of customers.
In conclusion, big data analytics is vital because it helps organizations to optimize their performance and efficiency.
Implementing analytics into the business models reduce costs by figuring the most efficient way to do business and predicting the success rate of new products and services.
Industries Benefiting from Big Data Analytics
Any business that functions on quick, agile decisions to stay relevant and competitive in the market combined with innovative products/services is most likely using big data analytics to its advantage.
Here the most common sectors that benefit the most using big data analytics-
- Retail
The retail industry is one of the ficklest sectors that changes every season. The sector is entirely dependent on creating customer-centric products.
Big data analytics is the best way to gain customer insights and their preference.
According to the study from IBM, 62% of retail respondents confessed to having a competitive advantage by using information and analytics.
With more online shoppers, keeping track of retailers’ needs is a driving factor in generating revenue.
Retailers must know what and when a customer needs a particular product. Keeping the stock available at the right time is what big data analytics attempts to do.
It meets the fluctuating demands of the customer without losing them. The analytics provides infinite information, from buying habits to social media and various other in-depth knowledge of the customers.
Big data analytics is preferred for predicting trends, and the success rate of new products that eventually boost revenues.
- Medicine
The medicine industry is incredibly dependent on specialized equipment to diagnose, assist and track various medical procedures.
Using big data analytics tools, the industry is able to improve health in several ways.
The compiled data of patients’ family history provides comprehensive views about their well-being, potential risk, and various in-depth information about their health.
In other cases, public health departments use big data and analytics to prioritize food safety inspections.
- Banking
Banking is getting immensely reliant on digital technology infrastructure, and now many banks are getting innovative by using analytics.
For instance, Bank of America uses Erica, a virtual assistant that applies predictive analytics and natural language processing to view banking transaction histories or information about potential bills.
Virtual assistance does more than transactions, it also provides insightful financial advice to customers based on their banking habits.
Now banks are offering, totally personalized ‘financial solutions’ to their customers. Big data analytics also help banks with detecting frauds.
- Transportation
Using big data analytics, customer journeys are getting more personalized and have a high chance of successful journeys.
Bus representatives inform travelers of the people on the given bus or reduce the distance the travels have to walk to board buses.
Not just in the bus sector, analytics is also used in the railway & air-travel.
On one hand, it is helping aero-plane companies in doing proactive maintenance of their various heavy equipment.
On other hand, by analyzing the data of their frequent passengers, they are able to roll out, various offers & new flights/connecting flights to the benefit of their customer.
In upcoming posts, I will explain various techniques & concepts like ‘Classification’,’ Clustering’, ’Exploration’, ’Exploitation’ , ‘Upper Confidence Bounds with clusters’ ,‘ Behavior Constrained Thompson Sampling….etc.
Hope you got most of your Questions Answered regarding
What is Big Data Analytics and Why is it so Essential?
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