We offer a variety of professional & technical services that leverage Artificial Intelligence (AI), Data Analysis and Visualizations. We create optimized solutions by integrating technologies to solve any business challenge.
Capitalising on profesional expertise in implementing solutions for various markets with a strong data integration and cloud computing capabilities for large and complex projects
As an Agile development company, SRITECHALLAINCE’S mission is to perform rapid prototyping to tell you the best data story well in advance to beat your compititors.
Our team has an in-depth understanding of database design principles and the different types of databases (e.g.,relational, NoSQL) which is essential to create a perfect model for the given industry.
We have the ability to work with your data, identify patterns and trends to extract insights that can be communicated visually and are proficient in trending visualization tools like, Tableau, Power Bi, IBI, Qlik sense.
Our team of experts breaks down the silos within your own organizations data focusing on the most important and relevant data points with clear and easy to understand visuals. This avoids clutter and displaying irrelevant or redundant information.
The pricing plans are tailored per industry and the solution you are choosing and based on your defined strategies.
Business intelligence (BI) refers to the tools, technologies and practices used to analyze and transform data into meaningful and actionable insights that can help organizations make informed business decisions.
Data analytics involves the use of various statistical and quantitative techniques to analyze and interpret data, with the goal of uncovering insights and trends that can inform wise business decisions.
BI and Data Analytics are related fields, but they have different focuses. BI is more focused on generating reports and dashboards that provide high-level overview of an organization’s performance, while data analytics is more focused on using statistical and quantitative techniques to uncover insights and trends in the data.
Common data analytics techniques include descriptive analytics (which involve summarizing and visualizing data), predictive analytics (which involve using statistical models to make predictions about future outcomes),and prescriptive analytics (which involve using optimization techniques to make recommendations for actions to take).
A datawarehouse isa large, centralized repository of data that has been collected from multiple sources and is optimized for querying and analysis. Datawarehouses are typically used for business intelligence and reporting purposes.
Data mining is the process of discovering patterns and insights in large datasets. It involves using statistical and machine learning techniques to identify correlations, clusters and other patterns that can be used to inform business decisions.
Machine learning is a subfield of artificial intelligence that involves using algorithms and statistical models to enable computers to learn from data without being explicitly programmed. Machine learning is used in a wide range of applications, including predictive analytics and recommendation systems.
Big data refers to extremely large datasets that are too complex to be analyzed using traditional data processing techniques. Big data often involves the use of distributed computing systems and specialized tools and technologies to store, process and analyze the data..
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