Big Data

Big data, quite literally, is projected to be the next ‘big’ thing.

We’re all about big data right now. Big Data is the ocean of data now available to businesses via the social web, machine data and transactional data.

Question

Creative

Optimizing Spend

Simple

The big data varies in terms of volume

Big’ misconception: Big data is not for the small guy

According to a BMO Capital Markets report, $50 Billion is what marketers are spending on Big Data and advanced analytics in the hopes of improving marketing’s impact on the business.

Core Business Areas

With the help of big data, businesses strive to offer improved customer services, which can help boost profit. Enhanced customer experience is the principal goal of most companies.

Banking

Banks and retail tradesmen use big data for sentiment analysis and high-frequency trading, among others. The area also relies on big data for risk analytics and monitoring financial business activity

Insurance

The BFSI area largely implements big data and analytics to become more effective, customer-centric, and, therefore, more effective.

Financial Services

Financial companies use big data analytics to reduce overlapping, redundant operations as well as providing tools for easier access to data. 

Advertising

Use of big data helps in reducing fraud and allows the timely analysis of the record.

Marketing

marketing industry Use of big data helps in reducing fraud and allows the timely analysis of the record.

Retail

The retail industry gather a large amount of data through RFID, POS scanners, customer loyalty programs, and so on.

Features of Big Data Required for Business Data Collection

Collecting user data is the first step in the development of Big Data systems. There are many ways to collect user data, and most of them are performed without specific participation, or even experience, of users. While customers may carefully provide some personal data via surveys or feedback forms

Data Visualization: Visualization may be utilized for both classified data collected in the database. And the analysis results obtained using this information as a source.
Data Storage: Big Data solutions have greatly high demands for information storage capabilities as they have to store both collected raw data and processed data
Data Analysis: In order to make use of gathered data, it must be subjected to comprehensive processing that utilizes important computational resources.