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The world is changing and the era of Big Data is emerging with full force. Every business today realizes the need and significance of higher amounts of data pertaining to their existing and potential customers. Marketing used to be one of the most imperative activities that any business undertook in order to attract more and more customers. However, the scenario has completely changed today.
Along with marketing, there is a reasonable requisite of understanding the behavior of customers, what they want and how they want it; in order to design personalized marketing strategies capable of generating great results. Big Data can facilitate all of this; so let’s first understand what Big Data is?
Big Data can be simply defined as a large collection of data, structured and unstructured both, collected from a broad spectrum of sources. Big Data, in every way can help businesses to gain useful insights which can support better analysis and decision making by taking into consideration colossal amounts of heterogeneous data.
Typically, the following types of data come under the Big Data:
- Traditional Enterprise Data – It includes information about customers from company’s CRM systems, web store transactions, transactional ERP data and general ledger data.
- Social Data – This includes data from social media platforms and micro-blogging sites like Facebook, Twitter etc. It also includes customer feedback streams.
- Machine Generated or Sensor Data – This type of data comes from trading systems, equipment logs or digital exhaust, manufacturing sensors, smart meters, weblogs, CDRs (Call Detail Records) and many more.
As we talk about Big Data, the first and foremost characteristic of it that strikes to mind is large volume of data as it is the most visible parameter. However, volume is not the only characteristic associated with Big Data. There are three more characteristics, which determine its credibility. The four major characteristics of Big Data include:
The machine generated Big Data is produced on a very large scale as compared to its non-traditional counterpart. For example, a single jet engine can generate around 10 TB of data in half an hour. Imagine how much data would be generated by over 25,000 airline flights in a day. The data volume reaches to Petabytes. Other sources like mobile, through the social media interactions also produce loads of data.
Velocity, in very simple terms, refers to the frequency at which data is getting accumulated. The social media data streams do not produce data as massive as machine generated data, but certainly contribute to Big Data with a large influx of opinions and relationships valuable to CRM. Even if we consider the smallest tweets, they are tweeted with very high velocity and they contribute over 8 TB of data on daily basis.
The traditional data formats used to have a propensity of being well defined by a data schema and used to change very slowly. But, their non-traditional counterparts exhibit a very fast rate of change. As new sensors are being deployed, new services are getting added and new marketing campaigns are being executed, newer data types are required to capture the essence of the whole information.
Value is the last but most important characteristic of Big Data. The fiscal value of various types of data that come under Big Data varies considerably. Characteristically, there is a lot of good information, which is hidden, in a very large volume of non-traditional data and the biggest challenge is to identify which information is valuable.
Once identified, the next challenge is to extract and transform that data for analysis.
How to use Big Data?
In order to derive value from Big Data, enterprises are required to evolve their existing IT infrastructure to handle large amounts of high variety and high velocity data and integrate them with the already existing enterprise data, to analyze them and derive valuable results from them.
Significance of Big Data
When Big Data is distilled and then analyzed after combining it with traditional enterprise data, enterprises become capable of developing a profound, insightful and thorough understanding of their business and customers. This can certainly lead to a stronger competitive position in the market, greater innovation, enhanced productivity and above all an imperative impact on the bottom line improvement.
For example, the proliferation of GPS devices and smart phones offers an opportunity to the advertisers to target consumers exactly at the right time, like when they are in a close proximity of a store, a restaurant or a coffee shop. This certainly enhances the chances of generating bigger revenues and also gives a stronger chance to the businesses to target potential customers.
Similarly, the social networking sites like Twitter, Facebook and LinkedIn are strongly connected to Big Data in many ways. First of all, the business model of such social platforms needs a personalized approach, for which one has to rely on Big Data by using all the
available data about a member or a user. Secondly, these social networks themselves are great contributors in the accumulation of Big Data, which can be used by other industries.
One of the blooming sectors, which can derive great benefits from Big Data, is “Retail”. Use of web logs and social media from their ecommerce shopping portals can help them understand which user spent how much time navigating a specific product subcategory, who bought stuff and who did not, the pattern users follow while searching for products. This can help in developing more effectual micro customer segmentation and design the targeted marketing strategies, as well as improve supply chain effectiveness with the help of much accurate demand planning.
Other industrial verticals can also derive vital benefits from Big Data in order to improve their services for the customers and deliver what their potential customers are seeking. Healthcare, manufacturing, advertisements etc. are some of the leading fields, which are currently getting benefited through Big Data analysis.
Big Data started as a revolution and in the years to come it will become the most important segment of every business planning activity.
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