Why Should You Integrate Big Data Analytics with .NET?

The volume of data is increasing beyond our conception — everything is being recorded, captured, and saved, from our behaviors to our relationships to our seemingly limitless business/professional activity.

Every day, more than 2.5 quintillion bytes of data are generated, according to a DOMO study. Furthermore, it is predicted that by 2020, each person would generate 1.7 MB of data in a single second.

That is enormous! Isn’t that right?

Whether you are an IT services provider, a , or going to invest in a .NET development company, it is critical that you address the ‘data explosion’ aspect, as it will soon affect your clients if it hasn’t already.

This article discusses why incorporating Big Data is advantageous.

Today, millions of professionals from all sizes and industries rely on Microsoft.NET Development Services to create mission-critical applications.

The Advantages of Integrating Big Data Analytics with .NET

1. Improved Decision Making

2. Prompt Problem Resolution

3. Data Reliability

4. Cost-cutting

1) Improved Decision Making

When businesses connect Big Data analytics with.NET, they gain a platform for analyzing huge volumes of data (in real time), identifying patterns, and making data-driven choices.

Furthermore, because the platform designed is customer-focused, it effectively demonstrates its potential. To give a boost to your company,  and we guarantee you the best of .NET development services.

2) Prompt Problem Resolution

With the addition of Big Data analytics, organizations can use the solution to find more detailed answers to a variety of business queries, such as what their customers want, which segment to target, which new products to offer, who their best customers are, and why customers are turning to competitors.

Overall, the process of locating answers to complex problems becomes more efficient and speedy.

3) Data Reliability

Organizations can gain a more accurate perspective of answers by adding Big Data analytics into customer-specific question and answer processes (for example, surveys, feedback, and questionnaires).

Furthermore, the collected data can be coupled with client history (often received through cookies) for planning purposes.

4) Cost- Cutting

Big Data analytics allows for data compression at the most granular level, which not only decreases storage requirements but also reduces the number of nodes and simplifies the infrastructure.

Overall, the cost of data storage has been significantly reduced.

Bottom- Line

The.NET development community is currently focused on creating.NET apps with the ability to learn from data and extract insights. In reality, they are the apps that are in high demand in the business world.

Furthermore, by combining Big Data Analytics and.NET, enterprises gain a powerful tool for creating consumer profiles that can be used to drive digital strategy and build highly targeted advertising.



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