Data Mining and Analytics
Gyan Web Solutions' analytics team is constantly researching on analytic techniques of optimization, statistics, queuing theory etc. to improve processes and provide an ability to use actionable, data-driven business insight to meet business challenges.
Some of the several data mining techniques being used today include:
- Pattern Matching
- Data Visualization
Gyan Web Solutions provides industry-leading experts to address your data warehousing and business intelligence in three main service areas:
- Data Management and Architecture
- Data Acquisition
- Data Mining/OLAP
The need for a good data management and architecture is simply humungous- yet most firms' information technology leaders readily admit that there is much room for improved data management. Some of the most researched surveys and CIO mind-maps reveal that most of the today's CIO's are not successful in engaging and implementing an enterprise-wide content management strategy.
Gyan's Data Management /Architecture service empowers organizations by allowing you to harness your vast amounts of information to become more customer-focused and profitable. We help you assess, collect, maintain, analyze, and disseminate information using advanced data warehousing and decision support tools. Our services help you architect and design databases, create data migration processes and develop customized reports to meet your exact business needs.
Enterprise Data Warehousing
We pride ourselves in building data warehouses for many medium to large scale businesses encompassing a variety of business domains. Our work involves extracting data from a disparate data sources, legacy databases and transforming them in a relational format and storing them in Operation databases and also into data warehouses. The data in data warehouse is stored by subjects or dimensions relating to the business. Data is stored as snapshots over past and current periods. Data from the operational systems are moved into the data warehouse at specific intervals as dictated by business requirements. Data is summarized at different levels. You can then go to a particular level of detail and satisfy a query. Increase in data granularity needs a lot of data to be stored in a data warehouse so Gyan Web Solutions’ architects and business analysts analyze and recommend an architecture which suits the level of detail or data granularity required by the business.
Predictive Modeling and Big Data
Businesses today require advanced business intelligence solutions to make profitable decisions and gain an edge in the industry. Data and Information management to a very detailed and granular level are needed to provide actionable insights. We collaborate and offer a complete analytics solution for enterprises to leverage big data to make informative decisions and thus gain an upper hand in market.
We employ the following approach to provide a predictive analytics solution to our customers:
- A discovery phase to understand the business and how to gather "Big data" pertaining to the business and the industry as a whole
- Data preparation which may involve data clean-up, transformations, dissecting data into subsets of records etc
- Evaluate various models (e.g. regression models like generalized linear model, classifier algorithms etc.) against the business need and decide which best fits the case. Capacity control is a major aspect in model selection as the model should be big enough so that we do not miss any exploitable patterns, but not too big which can lead us to confuse pattern and noise
- Model deployment. Apply the model to data sets to derive predictions