Big Data

Data products are increasingly becoming a key part of various businesses and serve as the underpinning for many businesses decisions

What is it?
Why does it matters?

Big data is a term that describes large, hard-to-manage volumes of data – both structured and unstructured – that inundate businesses on a day-to-day basis. But it’s not just the type or amount of data that’s important, it’s what organizations do with the data that matters. Big data can be analyzed for insights that improve decisions and give confidence for making strategic business moves.

Speech Recognition

Aggregate structured, semi-structured and unstructured data from touchpoints your customer has with the company to gain a 360-degree view of your customer’s behavior and motivations for improved tailored marketing. Data sources can include social media, sensors, mobile devices, sentiment, and call log data.

Detect and mitigate fraud

Monitor transactions in real-time, proactively recognizing those abnormal patterns and behaviors indicating fraudulent activity. Using the power of big data along with predictive/prescriptive analytics and comparison of historical and transactional data helps companies predict and mitigate fraud.

Drive supply chain efficiencies

Gather and analyze big data to determine how products are reaching their destination, identifying inefficiencies and where costs and time can be saved. Sensors, logs and transactional data can help track critical information from the warehouse to the destination.

Analytical Workflow for a Data Science Project

Data Ingestion

Big Data Ingestion gathers data and brings it into a data processing system where it can be stored, analyzed, and accessed. Data processing systems can include data lakes, databases, and search engines.

Data Modelling

Data models are made up of entities, which are the objects or concepts we want to track data about, and they become the tables in a database. Products, vendors, and customers are all examples of potential entities in a data model.

Data Wrangling

Data wrangling is the process of cleaning, structuring, and enriching raw data into the desired format for better decision-making in less time. Data wrangling is increasingly ubiquitous at today’s top firms.

Visualization

Data visualization is the graphical representation of information and data. By using visual elements like charts, graphs, and maps, data visualization tools provide an accessible way to see and understand trends.

Report

Data reporting helps you track what's happening to your business and evaluate its performance. It's the process of collecting, merging, and visualizing raw data from all available sources.

Who's focusing on Big Data?

Big data is a big deal for industries. The onslaught of IoT and other connected devices has created a massive uptick in the number of information organizations collect, manage and analyze. Along with big data comes the potential to unlock big insights – for every industry, large to small.

When you combine big data with high-performance analytics, you can accomplish business-related tasks such as:

Determining root causes of failures, issues and defects in near-real time.
Spotting anomalies faster and more accurately than the human eye.
Improving patient outcomes by rapidly converting medical image data into insights.
Recalculating entire risk portfolios in minutes.
Sharpening deep learning models' ability to accurately classify and react to changing variables.
Detecting fraudulent behavior before it affects your organization.