What is Data Science?

Data Science is the science of finding patterns in data so that we can use them to provide better products and services to customers. It is often applied in the context of Big Data. Big data is a massive volume of both structured and unstructured data that is so large it is difficult to process using traditional database and software techniques.

Why has it become important now?

Cost Reductions

Data Science leads to cost reductions. Many organizations have found wastage by analyzing the data and applying the findings to improve their processes. Organizations have been able to reduce some of their costs to the tune of 10%.

Processing TIme Reductions

Data Science has been successfully used to determine root causes of failures, issues and defects in near-real time. It has also led to entire new business processes which get completed very fast. For example, generating coupons at the point of sale based on the customer’s buying habits and recalculating entire risk portfolios in minutes.

Introduction of New Products

Big data innovation is to share ideas and concepts on how to efficiently extract the knowledge & insights from data that we hold as organizations; big data scientific inquiry requires less reliance on existing knowledge.

Smart Decision Making

Topping the list of benefits realized from big data analysis are better strategic decisions (69%), improved control of operational processes (54%), better understanding of customers (52%).

Why Data Science matters?

Data Science is all around us. The massive volume of data which is being collected is worthless unless insights can be gleaned from it and converted into useful business outcomes. What good is collecting data about customer's site visits if it can not be used to increase sales or provide better customer service?

  • Data Quality

    We all know that garbage in leads togarbage out. A good quality data is the heart of good Data Science. We know how to make your perfect so that you get the best results.

  • Data Analysis

    After Data Quality, Data has to be analysed to identify those critical few features which are crucial to solving your business problems.

  • Data Driven Business Models

    The features identified are used to create a model which helps us predict the behaviour of your system and leads to better business outcome.

  • Visualizations

    Great visualizations help us not only communicate to wider audience but also help us more than what is out there.

What is the process of Data Science Model creation?

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Collect Data

2.7 Zetabytes (that’s 27 with 21 0s after it) of data exist in the digital universe today.
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Analyze and Create Model

By 2020 analysts predict the amount of data will be 50x what it is today.
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Fine-tune the model

In 2012 90% of all the data that existed in our entire history had been created in the previous 2 years.
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Every 2 days we create as much information as we did from the beginning of time up to 2003.

Our ambition was to show how we can use Data Sceince to improve peoples lives and day to day experiences