With exponential growth in data, there is an increasing need for companies to deal with collecting, processing, analyzing and interpreting this data to extract valuable insights and knowledge. By leveraging data science and analytics, companies can gain a competitive advantage and drive innovation, leading to increased efficiency and profitability.
Our team of Data Scientists and Analysts focus on creating methods for capturing, processing, and organizing data to uncover actionable insights for current problems, as well as establishing the best way to present this data through dashboards and reports intended to help organizations make informed decisions, understand consumer behavior, predict future trends, and optimize business processes leveraging on Artificial Intelligence and Machine Learning solutions.
Data science and Data Analytics are two of the most important aspects of the modern business landscape. Data science and analytics solutions are about making sense of historical data as well as developing algorithms using machine learning and predictive modelling to solve analytically complex business problems.
Know your Business Better with Data Analytics:
BigTapp’s data analytics consultants focus on creating methods for capturing, processing, and organizing data to uncover actionable insights for current problems, as well as establishing the best way to present this data through dashboards. This enables businesses to get a complete understanding of their business problems through descriptive analytics by getting answers to specific questions that require answers based on existing data.
Run your Business effectively with Data Science:
BigTapp’s Data Scientists use AI, ML and DL models that provide a variety of insights to businesses, such as customer segmentation, market trends, predictive & prescriptive analytics to understand customers better and take decisions based on accurate data. Data science can also help businesses develop cost-effective strategies, automate processes, and gain competitive advantages and can help businesses identify areas of improvement and generate new ideas. By leveraging Data Science, businesses can gain a greater understanding of their customers, markets, and operations, ultimately leading to better decision-making and more efficient operations.
The following are some of our key offerings in Data Science & Analytics:
Our Descriptive modelling offering uses Machine Learning to help organizations understand their data by summarizing its characteristics and patterns, which are essential for problem-solving and decision-making. By providing a comprehensive view of the data, descriptive modelling can assist with identifying trends, discovering hidden relationships, and improving business processes.
Predictive modelling uses AI and Deep Learning models to help organizations anticipate future trends and outcomes. Predictive models use historical data to identify patterns and relationships that can be used to make predictions. These models can be applied to various use cases, including customer behaviour, sales forecasting, and risk management. Organizations can make better decisions, plan for future trends, and optimize their operations by providing accurate predictions.
These models will help you with
As part of our Data Analysis offering, we help companies discover patterns and trends in the data using various techniques and tools and create visual representations of the data to make it easier to understand with the help of Data Storytelling.
The latter part focuses on presenting data tailored to a specific audience through an exciting narrative, without bias and with the proper empathy and context that humans can understand. Data is presented understandably and memorably using stories and graphics helping you with.
This offering focuses on presenting complex data visually through graphics, making it easier to spot patterns, trends, and correlations to facilitate better understanding. It bridges the gap between having lots of data and understanding it to drive actions and decisions. Data visualization helps you with.
Analytics operationalization is taking a concept, typically ML or AI predictive learning models, into production with live data that enables businesses to embed big data analytics into the daily workflow of operations, achieve a state of continuous improvement and achieve greater returns from analytics and big data investments. Data operationalization can be achieved through automated API-based integration, which helps to overcome technical challenges such as scalability, integration viability, model monitoring, maintenance, and portability.
The act of analyzing very large, diverse data sets from different sources and sizes to power better decisions is called big data analytics.. It helps organizations and teams lead more efficient products, services, and solutions. In this hyperconnected, highly competitive environment, businesses must make decisions faster than ever before to stay ahead.
Prebuilt models and scripts reduce development time and enable customized solutions, providing faster time-to-market and greater value to clients.
Strong machine learning and AI capabilities and a proven track record of successful data science projects establish credibility, build trust, and attract new clients.
Data science-based products like TalentTapp, Supply Quotient, and Info-Active demonstrate innovation and differentiate organizations from competitors.
Building embedded applications into enterprise applications enables customized solutions that integrate with existing workflows, improving decision-making and operational efficiency and providing a competitive advantage.
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