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Data Analytics

Welcome to the future of Data Analytics!

Data analytics (DA) is the process of examining data sets in order to draw conclusions about the information they contain, increasingly with the aid of specialized systems and software. Data analytics technologies and techniques are widely used in commercial industries to enable organizations to make more-informed business decisions and by scientists and researchers to verify or disprove scientific models, theories and hypotheses.

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Data Analytics initiatives can help businesses with


Ultimate goal of boosting business performance.

  • Increase revenues.
  • Improve operational efficiency.
  • Optimize marketing campaigns and customer service efforts UI
  • Respond more quickly to emerging market trends.
  • Gain a competitive edge over rivals.

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Augmented Analysis

Augmented Analytics automates data insight by utilizing machine learning and natural language to automate data preparation and enable data sharing. This advanced use, manipulation and presentation of data simplifies data to present clear results and provides access to sophisticated tools So business users can make day-to-day decisions with confidence. Users can go beyond opinion and bias to get real insight and act on data quickly and accurately.

Self Service Analytics

Self-service analytics is often characterized by simple-to-use BI tools with basic analytic capabilities and an underlying data model that has been simplified or scaled down for ease of understanding and straightforward data access.

Predictive Analytics

Predictive analytics encompasses a variety of statistical techniques from data mining, predictive modelling, and machine learning, that analyze current and historical facts to make predictions about future or otherwise unknown events.

Advanced Analytics

Advanced Analytics is the autonomous or semi-autonomous examination of data or content using sophisticated techniques and tools, typically beyond those of traditional business intelligence (BI), to discover deeper insights, make predictions, or generate recommendations

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Build a solid data foundation based on trusted, connected data

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Data management is the practice of organizing and maintaining data processes to meet ongoing information lifecycle needs. Emphasis on data management began with the electronics era of data processing, but data management methods have roots in accounting, statistics, logistical planning etc.

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Various online data storage platforms

Cloud storage

Cloud storage is a model of computer data storage in which the digital data is stored in logical pools. The physical storage spans multiple servers (sometimes in multiple locations), and the physical environment is typically owned and managed by a hosting company

Data lake

A data lake is a system or repository of data stored in its natural format, usually object blobs or files. A data lake is usually a single store of all enterprise data including raw copies of source system data and transformed data used for tasks such as  reporting, visualization, analytics and machine learning.

Data warehouse

DWs are central repositories of integrated data from one or more disparate sources. They store current and historical data in one single place that are used for creating analytical reports for workers throughout the enterprise.

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