DATA MINING

Help you to make well informed business decisions and improve your way of functioning.


Data mining is the computational process of discovering patterns in large data sets involving methods at the intersection of artificial intelligence, machine learning, statistics and database systems.

It is complex and time consuming process of sifting through large chunks of data to pick up data items that are relevant by weeding out erroneous and redundant data. An accurate and a highly relevant data base will help you to make well informed business decisions and improve your way of functioning.


TeslaWatt’s best online data mining services include:

  • * Web data mining
  • * Data extractions
  • * Text mining
  • * Screen scraping
  • * Data warehousing
  • * Product registration data mining
  • * Shipping documents mining

These services follow standard practices of classification, clustering, regression and associated rules of data mining.

TeslaWatt provides data mining services that you can use to make accurate forecasts and predictions such as web service mining, mailing list creation, database mining, latest news summarization, prediction data mining and much more.

Comprehensive Data Mining/Extraction Services

Our standard operating procedures combined with the experience and expertise of our data professionals ensure that we can quickly and efficiently process millions of records without compromising on quality or accuracy. Our unparalleled level of customer support means that we’re here to support you whenever you need it.

  • * Collecting information from different sources
  • * Populating information into desired output formats like CSV, MS Excel, MS Access, and MS Word etc.
  • * Checking product details and updates like prices, rate comparisons, product listings, product descriptions and product availability, product images and product catalogs and feeding them onto a content management system or an online portal.
  • * Gathering financial data, identifying patterns, correlations and expectant future trends, analyzing competitor standings, locating dependency networks, evaluating market changes, building product catalogs and generating potential sales leads.
  • * Establishing the relationship between internal (price, product positioning) and external (customer demographics, competitor analysis) factors.
  • * Creating mailing lists for marketing campaigns and advertisements.
  • * Clustering information, creating information repositories and combining multiple databases to make a data warehouse.