Data & Analytics

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In God we trust, all others must bring data.


– W. Edwards Deming

Business Intelligence & Analytics

Businesses are finding ways to use Big Data insights to stop credit card fraud, anticipating and intervening hardware failures, rerouting traffic to avoid congestion, and guiding consumer spending through real-time interactions and applications.

But despite the hype, businesses struggle to make use of the data they collate due to a huge gap between the theoretical knowledge and actually putting this theory into practice. A few big data problems – data complexity, data silos, inaccurate data, advanced technology and lack of talent.

With a multi-disciplinary approach including Big Data techniques:

  • You can discover trends, predict when they will occur, and possibly change the future occurrences.
  • You can verify correlations between people, places, genes, environment, products, the environment and much more.
Big Data

In todays world, with so much of data trail left behind with every transaction, its hard to ignore this data and not base future decisions on them.

BI consists of answering questions such as “What happenned”, “How Often has it happenned”, “When did the events occcur” etc. BI is built over traditional transaction and warehouse data sources and is an excellent means to measure past performance. Advanced reporting engines, visualizations, dashboards typically form the frond end of the applications.

Analytics goes a step beyond BI and involves modeling techniques to predict events based on past patterns. Analytics can help answer questions such as – “What can happen”, “Why will it happen”, “What will happen if something else also occurs”. Analytics is often a process of connnecting the dots and by taking into consideration seemingly disparate parameters in relation to each other. The data sources under consideration are both structured and unstructured.

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