The Beginner’s know-how to Big Data Analytics

by Guest Author on January 15, 2020

in Guest Posts

Big Data is a software-utility technology used to capture, store and analyze large volume of data collected from multiple sources for enhanced decision-making.

Big Data Concept

Big Data terminology explains storage and analysis of complex and high volume data that is practically impossible to process by human brain. Therefore, this software-utility technology emerged as a solution to comprehend high velocity data to provide deeper insights and enhance decision-making process. To simply put in layman language, it is nothing but collection of large volume data. Nowadays, companies are focused towards customer-centric approach to offer premium product/ service quality and support. This can be very-well possible when the information comes from the horse’s mouth. And, no one can be better at it than your target customer itself. Big Data lets you capture and store information of your buyer persona through his/ her social media accounts, cookies, buying history, interests and behavior, demography, geography and many such attributes.

Big Data and Analytics Correlation

Analytics have always existed. For most of the years, analytical techniques like text, statistics, diagnostic, predictive and prescriptive analysis have been used over and over by companies around the globe to understand the patters and behavior of buyers. However, the data to be analyzed in traditional times was limited. But, in contrast to older times, the present day produces data in numerous facets that is hypothetically impossible to analyze manually. This is when big data comes into the picture. Its potential to handle humongous volume of data helps users get a unified view to diversified information through a single channel. Big Data Analytics deals with analyzing three types of data – high volume, high velocity, and high variety. A company therefore, can tackle depending on its quantity, speed, and type.

Key Big Data Analytics Technologies

  1. Data Mining: To address delicate business concerns, it is vital to discover patterns and which efforts reaped benefits, while which went down the drains. Data mining helps in removing redundancy and present the relevant information alone to boost the decision-making speed.
  2. Text Mining: Various interactions being carried out on social media, SMS and emails can be used to identify buyer behavior and buying pattern. This helps in mitigating the bounce rate and leveraging relevant traffic and engagement.
  3. Predictive Analysis: Using machine learning techniques and statistical analysis, it is possible to anticipate future outcomes on the basis of historical data. This can save companies the actual damage that could happen by literally experiencing the mishap in person.
  4. Hadoop: It is an open source framework that is used to store and deploy massive amount of data on hardware. This computing model offers a quicker access to data and its different varieties. This helps companies save time and increase efficiency.

Key Benefits

  • Data can be captured even through an unstructured source
  • There is no limit to whatsoever data you want to capture
  • This will help you get insights about potential audiences at your fingertips
  • Marketing teams can create better demand generation strategies
  • Sales and customer service representatives can identify the historic communication trail
  • Data can be stored in various types and forms
  • Even the highest speed data can be captured and stored
  • It is possible to facilitate predictive analysis to save future damage

Conclusion

Big data organizes massive amount of data in structured and unstructured format through eclectic sources like social media, website, emails, audio-video clips and text files to comprehend and analyze this data in real time for enhanced productivity. CRM- customer relationship management software services in India allows facilitates data analysis, segmentation and execution. As a marketer, big data can play a strong pillar in creating demand generation strategies, since it is easier to segment similar audience behaviors in a segment. Big data has a bright future and companies should not let its potential go ignored.

Guest article written by: Kalyani writes about upcoming technologies like big data, machine learning, virtual reality, AI and robotics. Her expertise lies in growing the business opportunities by market qualified lead generation through inbound (SEO, content marketing, PPC, social media, email marketing) and outbound practices. Kalyani works for Sage Software Solutions Pvt. Ltd., a leading provider of CRM software to small and mid-sized businesses in India. You can learn more about her on Twitter | LinkedIn

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{ 3 comments… read them below or add one }

Vibhuti Singh January 16, 2020 at 09:49

Hey Kalyani,
What an insightful post! I appreciate that you took a clear and concise way to get into the crux of big data concepts.

I agree with your point that big data has a lot to offer – not only in terms of providing vast chunks of gainful data but also elevating and adding value to the brand interaction with customers. On the other hand, as it is ever-evolving and growing, challenges like storage, data integrity, and data privacy must be surmounted to harness its utmost potential. I can’t wait to see how big data field will progress in the coming years.

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David Smith January 16, 2020 at 10:15

Hey Kalyani,
What an insightful post! I appreciate that you took a clear and concise way to get into the crux of big data concepts.
I agree with your point that big data has a lot to offer – not only in terms of providing vast chunks of gainful data but also elevating and adding value to the brand interaction with customers. On the other hand, as it is ever-evolving and growing, challenges like storage, data integrity, and data privacy must be surmounted to harness its utmost potential. I can’t wait to see how big data field will progress in the coming years.

Reply

Rafaela Luna January 17, 2020 at 04:19

Thank you for sharing this educational article! I admit I acquire only a little knowledge about Big Data Analysis and this article gave me a new perspective. A clearer one. I doubt if it has relevance in today’s era thus, I confirmed it now that I have read this. Thanks, Kalyani!

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