Big Data & Analytics

Prominent IT assists clients in uncovering strategic opportunities from the heaps of internal and external data. The focus is on solutions evaluation, enhancing e and integrating data to transform it into actionable insights.

Prominent IT expertise lies in:

End-to-End Capabilities from Process Analysis and KPI identification to, of course, Development

Dedicated team of Certified BI Consultants

Experience in a Full Range of Tools/Products that do Include: SAP suite, Cognos, Oracle, Qlikview, as well as Microsoft

Experience in providing Analytical as well as Predictive modeling expertise with the use of tools such as SAS , R Programming, Python , PowerBI, Tableau etc

Strong Knowledge of applying Data Warehousing cum Data Modelling to solve complex data challenges

Analytics is the systematic computational analysis of data or statistics. It is used for the discovery, interpretation, and communication of meaningful patterns in data. It also does involve applying data patterns to affect decision-making. It can also be valuable in areas rich with recorded information; analytics relies on the simultaneous application of statistics, computer programming, and operations research to quantify performance.

Process of Big Data & Analysis

Big data analytics involves collecting, cleaning, processing, and analyzing large datasets to help organizations operationalize their big data. Prominent IT is fully aware of this.

Data collection does appear different for every organization. With today’s technology, organizations can gather both structured as well as unstructured data from a variety of sources — from cloud storage to mobile applications to nearly in-store IoT sensors as well as beyond. Some data can be stored in data warehouses where business intelligence tools cum solutions can access it easily.

After data is collected and stored, it must be appropriately systematized to get accurate results on analytical queries, especially when it is significant and unstructured. Available data is increasing quickly, thus making data processing a challenge for organizations. One processing option can be batch processing, which does appear at large data blocks over time. Batch processing is beneficial when there is a longer turnaround time between collecting and analyzing data. Stream processing does appear at small batches of data at a particular go, thus shortening the delay between collection and analysis for quicker decision-making. Stream processing is more complex and often more expensive.

Data, big or small data, requires scrubbing to improve data quality and get more robust results; all data must be formatted correctly, and any redundant or irrelevant data must be eliminated or accounted for. Dirty data turn out to be obscure and misleading, creating flawed insights.

Getting big data into a usable state does take time. Once it is ready, advanced analytics processes can turn big data into significant insights. Some of these essential data analysis methods do include:

  • Data mining sorts via large datasets to identify patterns and relationships by identifying anomalies and creating data clusters.
  • Predictive analytics does use an organization’s historical data to make predictions, identifying upcoming risks s well as opportunities.
  • Deep learning imitates human learning patterns by making use of artificial intelligence cum machine learning to layer algorithms and also helps find patterns in the most complex as well as abstract data.

Benefits & Advantages of Big Data Analytics

  • The process of converting large amounts of unstructured raw data can be retrieved from different sources to a data product made useful for organizations forming the core of Big Data Analytics.
  • Quicker as well as Better Decision Making within the Organization
  • Big data analytics’ speed and efficiency are the highlights of ensuring that big data has become a sensation recently. Today, businesses would take months to make a strategic decision based on data analytics.
  • Improvement of Customer Experience. Big Data analysis benefits in improving customer experiences.
  • Big data is a substantial volume of data and datasets that come in diverse forms and from multiple sources. Several organizations do recognize the advantages of collecting as much data as possible.