We offer Analytics Solutions related to Static Analysis, Real Time Analysis and Predictive Analysis
Our Experts create solutions to add intelligence to your business by transforming raw data into decision making reports with nice presentation.
Our Algorithms learn your business faster using the Machine learning techniques so as to predict the customer behavior and patterns
Your raw data is well maintained through a structured pipeline into a value added reports and analytics
Organizations are grappling with a deluge of raw data, and analysts estimate that 80% of it is unstructured, file-based and cannot be analyzed with traditional relational database tools. This data might seem unwieldy – but with the right analytics, it has the potential to increase productivity, improve decision-making and positively disrupt businesses.
Business intelligence (BI) represents the tools and systems that play a key role in the strategic planning process within a corporation. These BI systems allow a company to gather, store, access and analyze corporate data to aid in decision-making.
Generally these systems will illustrate business intelligence in the areas of customer profiling, customer support, market research, market segmentation, product profitability, statistical analysis, and inventory and distribution analysis to name a few.
Machine learning is a method of data analysis that automates analytical model building. Using algorithms that iteratively learn from data, machine learning allows computers to find hidden insights without being explicitly programmed where to look.
Data may be your most valuable resource. It’s certainly not an endangered one. It pours into organizations from every conceivable source – operational and transactional systems; scanners, sensors and smart meters; inbound and outbound customer contact points; mobile media and the Web.
Data access refers to your ability to get to and retrieve information wherever it is stored. Certain technologies can make this step as easy and efficient as possible so you can spend more time using the data – not just trying to find it.
Data quality is the practice of making sure data is accurate and usable for its intended purpose. This starts from the moment data is accessed and continues through various integration points with other data – and even includes the point before it is published or reported.
Data integration defines the steps for combining different types of data. Data integration tools help you design and automate the steps that do this work.