Transform your business decision making with Big Data Analytics

Business is an art and to crack the deal is the big step in the market. While most companies are fighting for customers, it is a smart businessman who believes in marketing. The big decisions that a business should make may involve the target audience. A business should always focus on who the target audience is and what they actually want. With data analytics, one can make virtuous decisions. But before moving forward let’s understand what is Big data analytics

What is Big Data Analytics?

Big data analytics is a complex process. It involves discovering hidden patterns, market trends, and audience preferences. Companies today are flooded with data. 90% of the world’s data was created in the last 2 years alone. That’s why 85% of business leaders believe that big data will revolutionize business the way the internet did. But there’s is a big gap between data and decision making. Why is it so hard to turn this ocean of information into actionable insight?

It boils down to 4 things:

First, many analytics firms take a black-box approach to technology crunching your company’s historical data and spitting out a prediction. But their models are so insular, complex, and backward-looking that you often get the what of a prediction without ever getting the why.

Second, the approach to data isn’t organized. Most analytics companies start their worth once the data has been provided to them. But your data is rarely housed in a central easy to manage way. It takes a lot of time to pull that data together and once we do the data may be messy, unreliable, and siloed. To top it all off, that data is changing constantly.

Third, many companies use inappropriate deployment that lacks visibility they either use an expensive and time-consuming custom approach or a clunky one-size-fits-all approach. Both keep you in the dark about how the results were achieved.

Fourth, Big data requires a lot of people and resources. A top-performing team will include data engineers, data analysts, data scientists, domain experts, and business process experts. And most companies just don’t have the resources to bring all these skill sets to bear on Big Data projects.


At Insight International, we take you out of the black box, with an open and collaborative approach to big data analytics. We combine manpower, data science, user experience design, and big data analytics to create a pre-configured solution that can be quickly deployed easily customized, and constantly monitored. This brilliant platform helps you break down those silos in your organization to discover why what is next to your data is responsive, productive and efficient, and effective. That’s big data with Insight International.



Benefits of Data Analytics

There is a lot of business ease with data analytics. With the development of technology and methods, it has become easy to track a business’s growth. Here are some benefits of using big data analytics:

  1. Cost reduction: If the business doesn’t bring good revenues then it isn’t a business anymore. That’s where analytics comes into the picture. It reduces the chances of losing that business and brings fruitful results.
  2. Faster, better decision making: By looking at the analytics, it is easier to calibrate the consequence of a decision. That’s why decision-making becomes easy and quick.
  3. New products and services: Bringing new and customer-driven products brings the business closer to success. It gives a personalized feel to every product and that in turn increases the analytics.


Most organizations focus on delivering the matrix today, they should plan the customer-driven marketing strategies, that are satisfying the customer’s requests. Many businesses are focusing on the products as per the customers helping the business grow all together. But how do we analyze what customers need? That’s where Insight International steps in. We guide to big data analytics. We discover ways and methods to tackle business stress and challenges.



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Insight Inc April 12, 2021 0 Comments
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