A Software Development Company That Has Experience In Big Data Analytics

In a phenomenal way, technology has changed the way people live. One of the biggest tech trends today is big data and big data applications. It drives the world and pressures organizations to have a strategic approach to analyze data, to make better-informed decisions. It means bigger opportunities as well as challenges. It’s characterized mainly by its variety, volume, complexity and variability of information. Nonetheless, the volume isn’t the focus area since what’s important is its use to answer customer queries by becoming more data savvy.


In the digital age today, big data is abuzz in every enterprise wherein marketers are making significant use of it to boost the customer experience, improve customer interaction, lower costs, boost revenue and engage customers in numerous ways. The system could be analyzed to check for newly launched services in the market or its benefits and what opportunities still exist in the market. Sales persons could adopt the technique to find valuable prospect as well as expand current opportunity.

Big data could be described by these characteristics:

  1. Volume. The quantity data that’s generated and stored. The size of data will determine the value as well as potential insight and if it could actually be considered big data or otherwise. 
  2. Velocity. In this context, the speed in which data is generated as well as processed to meet the challenges and demands, which lie in the path of development and growth. 
  3. Variety. The nature and type of data. This helps those who analyze it to use the resulting insight in an effective way. 
  4. Veracity. The quality of data captured could greatly vary, which affect accurate analysis.
  5. Variability. Data set inconsistency could hamper processes to handle and manage it.



There are many service providers that provide experience data analytics solutions and services, such as TatvaSoft. It provides advanced solutions to a wide range of industries. Data experts understand the challenges and thus, as experienced professionals, they use the power of data analytics, domain expertise, skills and knowledge of big data analytics tools to fulfill business requirements, which result in successful outcomes.


In the highly competitive world today, data access and use in every business has become crucial to understanding customers and to take on decisions wisely. Customers demand a seamless experience across all channels, from basic search to transaction completion. The trend has changed the retail rend to customer-centric. Using data to understand the behavior of a customer, enabled implementing a targeted marketing campaign. Each business wants to connect with customers, regardless of their location, provide personalized service, but doing so holds a competitive challenge. Thus, collecting numerous data chunks will determine customer’s behavior. The data gathered from mobile, social media and local have been generated in an unstructured manner, which could not be managed by data warehouse ad business solutions. This gives birth to the need of data analytics solutions through which businesses could leverage the data available and drive marketing campaign, income and run a business effectively. Also, this provides an opportunity to understand dhow a customer is connected with the business.


Businesses demand granular data to understand the behavior of a customer. To make technology easier for customers to gain a seamless experience, retailers have the tendency to leverage the new trend to move change their cultural habit and acquire insight of the technology more as described here,
  1. Stock prediction. Predicting stock was a simple process because of limited data elements wherein shopping was limited to a few occasion or seasons. Big data provides limitless opportunity to predict stock ahead of variables, including weather, seasons, trends and more. Now, retailers could focus on selling only the product, instead of analyzing stock.

  2. Fuzzy logic. The concept denotes identifying the relationship between various data elements. For instance, a customer is sure about a product requirement, but not exposed to a few options before. On the other hand, retailers do not have the same product that customers wanted, but have something that’s the same for the  customer to search to gain their trust.

  3. Customer rewards. Big data enables retailers to keep track of returning customers that serve as a valuable resource for the business. To please customers and keep them engaged with the brand, the company offers loyalty rewards to every loyal customer. Analytics play a key role in loyalty programs through studying the behavior of the customer as well as the shopping pattern. It’s become effective in determine CRM strategies.

  4. Fraud detection and prevention. When a business goes online, detecting fraud becomes a main concern. As transactions go online, sophisticated fraudulent activities will begin. Data analytics gathers all unstructured data and analyzes it to determine mismatched patterns early on.

  5. Enhanced Shopping Concepts. Knowing what the majority of customers want or what they abandon in the shopping cart is a much needed insight for retailers. Big Data Analysis is a smart way of understanding shopping behavior and redefining the shopping process. Through leveraging in this technology, a retailer has access to customer interest, location near their stock location and can suggest a better deal to customers.

With Big Data analytics, companies could measure the spending and stay focused on the target. Companies could create marketing campaigns that would keep the audience more engaged. Since data analytics include structured and unstructured data gathered from various sources, one should be able to understand and to sort out useful data that has to be analyzed and stored. This would also need a big bunch of technical knowledge as well as disk space. Skilled big data analytics workers could make full use of the technology and work with the latest tech trends. Data scientists have sound knowledge and capable of taking decisions with the help of data. Furthermore, they are technically wise and could analyze data that comes from various sources and find data that is best suited for an organization.

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