The Big 6 Steps Of Big Data Explained

big data analytics

The world population as on October 2017 was 7.6 Billion people. Which directly points to the fact that this is Big Data! All the insights you receive from running digital campaigns is your big data! It is not manually possible to keep a tab on everyone who has viewed or is interested in your campaigns. The online method of data analysis is known as big data analytics. It is meant for all big or small businesses.

This blog will enlighten you with:

  1. What is big data?
  2. Top 6 steps of big data
  3. How big data and marketing work hand-in-hand?
  4. Some useful examples for your understanding

What is Big Data? 

It is voluminous information or relevant statistics acquired by companies, firms and large organizations. Often this big data is difficult to compute manually. Hence many software and data storages (computers, servers, etc..) have been formulated.  It is not “all things numbers” or volume it comprises of the 4V’s:  

  • Volume – It is the quantity of data gathered, generated and stored.  
  • VelocityThe speed at which all this data is received and also acted upon.  
  • Variety – Variety refers to how this continuous inflow, nature, and type of unstructured data.  
  • Value – Every bit of information received has value. To dig deeper multiple quantitative techniques for unstructured data is used.   

The above 4 V’s of big data is crucial for gathering, storing, analyzing, managing and consuming huge sets of information. These sets go beyond the traditional data computation.

big data analytics

The Big 6 Steps 

Data Mining 

There are two focus terms: data extraction & data mining. If simply put, data extraction is a process of collecting all data from web pages into your database. Whereas, data mining is a process of identifying valuable insights within that database. Such data is collected by data scientists.  

For example, you are an e-commerce grocery site owner. After using various research techniques, you concluded that approximately 70% people wear jeans. This is called data extraction. Now you have to go deeper to understand which age, gender, and type of people use Brand 1 and Brand 2 jeans. This process is known as data mining. Some of the useful data mining tools include RapidMiner, TeraData & Kaggle 

 Data Collection 

Big data doesn’t have an “END” button. As the world grows, data will keep on streaming in. Data needs to be extracted constantly. From the above example: there will be people who wear Brand 1 have switched to Brand 2 and so on. The possibilities are endless! Data extraction becomes easier with tools like 

Data Storing 

Ever imagined how Google must be storing so much of world data? Of course not on traditional systems – files, CDs, DVDs, etc.. Google, Facebook, Apple, on hyperscale computing environments. Which type of storage you should use depends on the scale of your business. A good data storage system provides an infrastructure which has all the latest data analytics tools and storage space. You can store your data on data storage providers like Cloudera, Hadoop (not for beginners) and Talend. Data storage is one step which here on can be inserted in between any other step.  

Data Cleaning 

Data sets can come in all forms and degrees – some good and some not so good especially if extracted from the web. Therefore, all the data extracted needs to cleaned. In the cleaning process, all the unwanted and inaccurate data is filtered out. After this process, you will only be left with what you actually want to focus on. Cleaning promotes structuring your data well. For example, you know number and type of people wearing jeans all over. While cleaning,  you can remove all the duplicate entries, wrong data, unwanted regions or information and more. You can make use of DataCleaner or OpenRefine for this purpose 

Data Analysis 

The biggest part of big data is the analytics! What is big data analytics? While analyzing the data you come across your audience pattern, behavior and so on. Exploratory research method proves to be very helpful in analyzing big data. Analytics is about asking a specific question and finding answers to it. Qubole and Statwing are powerful data analytics tools. For example, you might ask – does my audience like to wear two pocket jeans? Which color is most preferred by them,etc..  

Data Consumption 

Data is consumed in various verticals which include:  

  • Identifying retail trends in the market using which businesses can highlight their top selling products.
  • It is used by Government bodies in order to reach out to the correct demographics, geographies, and ethnicities.  
  • Marketers find big data extremely useful to figure out which advertisement works for their products.  

Big data is consumed at many places depending on the specific goals you want to achieve.  

Big Data & Marketing  

Marketing strategies largely rely on big data. Successful marketing strategies require data in order to provide best services to their target audience. Hence big data and marketing go hand-in-hand. Big data has amazing benefits such as: 

  • Understand your target audiences well 
  • Roll in the best price, product, and service strategies 
  • Send relevant messages to the audiences 

Big Examples 

  • Election representatives Barack Obama and Narendra Modi made optimum use of big data by targeting the right respondents. They were rewarded with victory in return.
  • Fact: eBay produces 50TB of machine-generated data and processes 100PB data using leading data analytics software to leverage it for analytics.  

Gain more insights and grow your business with PayUmoney now!

Author: Kinjal Shah

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