According to studies by Forbes, almost 1.7 MB of new information is produced every second. This only means that we are consuming more data than ever and data is in fact everywhere. All this data right from your photos to the organization’s financials has begun to be analyzed to produce valuable insights to the business.
Business Analytics as a field is buzzing now with great career prospects. Once you get the art of data analysis right with the help of business data analysis courses, it is just a matter of practising those skills to become a pro. However, off late another term “big data” is in the limelight.
So, what is big data and how is it different from business analytics?
Also Read: Kickstart your Career in Analytics with Data Science Program
Let’s see:
A Closer Look at Business Analytics
When it comes to business analytics, it encompasses approaches or technologies that are used to access and explore the company’s data. In other words, it measures the financial and operational metrics of the business with a view to producing valuable insights to aid business planning and performance.
Typically it employs statistical analysis and predictive modelling in order to establish trends – figuring out why it happened and making an educated guess about how things will pan out in the future.
Also Read: How to Build a Successful Career in Data Science?
What about Big Data?
Big data is high-volume, high-velocity and high-variety information that gets processed and analyzed. It refers to an immense volume of both structured and unstructured data that is aggregated and processed with automated tools or technologies.
To put it simply, Big Data analytics finds insights that aid organizations to make better strategic decisions. Big data assimilates all the data it can, for example, thousands of attributes of a single customer and then sets out to figure the behaviour of a customer – what they want, what will they do next time, how much they will spend.
What is the Difference between Big Data and Analytics?
Business analytics focuses on one core metric and that is the financial and operational analytics of the business. On the other hand, ‘Big data’ analytics helps to analyze a broader range of data coming in from all sources and helps the company to make better decisions.
Moreover, big data involves automation and business analytics rely on the person looking at the data and drawing inferences from it. In big data, the machine largely takes over the job of analytics.
Let’s take an example to understand better. In business analytics, we can keep track of the number of site visitors and few sales metrics to understand if a specific ad campaign had its intended effect. But in big data, you can gather all the information from several sources about a specific customer to understand their behaviour and thereby enabling the business to undertake strategic directives.
Whether it is Big Data or business analytics this is the time of exploiting data-specific opportunities in the market. Become a data expert with a business analyst course online.
Also Read: How can I pursue a Career in Business Analytics in 2022?
Some differences between Big Data and Analytics
Big data and analytics are two buzzwords that are splashed across various places. Companies like Facebook, Amazon, Apple and Google have been spending millions of dollars on big data and analytics. From a layman’s perspective, there might not be much difference in both. However, ask the experts and they will tell you that both these concepts stand on the far ends of the spectrum.
So, if you are inclined towards a career in these fields or add one more competency to your existing skill set, you need to understand how they differ from one another. A big data and analytics certification program would be good to start with. However, the below information will also give you a basic foundation in the concepts and explain their differences.
By Definition
What is Big Data?
Big data is a huge volume of structured and unstructured data that is generated every day, around the world. And, we are talking about quintillion bytes a day! Yes, you need to do a bit of math to find out where quintillion stands. However, this data is so complex and mind-boggling that it becomes almost impossible to analyze them manually or basic data management tools and applications.
What is Analytics?
Analytics is a systematic computation and interpretation of big data using statistics, mathematics, machine learning and predictive techniques. It is a scientific process to convert raw big data into meaningful information for useful insights and decision-making.
Inherent Difference
Big data differs from analytics on three major Vs:
Volume: The amount of data is generated from various sources such as social media, business transactions and machines.
Variety: Data comes in various formats – structured, unstructured, text, video, GPS, emails, websites, etc.
Velocity: The speed at which data is generated makes all the difference to decision-making and competitive advantage. The more real-time it is, quicker and timely the decisions can be taken.
Depending on how big data is generated on these three V’s, analytics can define necessary metrics to measure it. Only when an organization leverages these three V’s effectively, can its analytics become more robust.
Machines v/s People
At the end of the day, machines generate big data, but it is people who are required to do the analysis. There are data specialists who pour into spreadsheets for hours and do all number-crunching to provide insightful information to decision-makers. So, while computers and machines stay in the background mining data, data interpreters work on the front foot to analyse it.
Now that you know the difference, a data analytics certification course can further add to your knowledge and necessary skills.
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