Big Data Analytics Services

Big Data Analytics Services is the process of inspecting data sets to draw conclusions and improve systems in software. Big Data Analytics Services covers applications ranging from Basic Business Intelligence (BI), Reporting, and Online Analytical Processing (OLAP) to more advanced analytical features. By focusing on business users, Big Data Analytics Services initiatives can help companies increase revenue, operational efficiency and responsiveness to market trends. The data analyzed may contain historical records or new information, from internal and external sources.

Big Data Analytics Services methodology includes Exploration Data Analysis (EDA) to look for patterns and Confirmatory Data Analysis (CDA) to test hypotheses. There is quantitative and qualitative data analysis, with a focus on numerical or non-numeric data. Big data analytics services help businesses process and analyze large volumes of data to gain valuable insights. There are four main types of big data analytics services:

1. Descriptive Analytics:
   Descriptive analytics deals with the past and uses historical data to understand what has happened in a business. It involves summarizing and interpreting historical data to identify trends and patterns. Descriptive analytics answers the question "What has happened?" and is often used to create reports and dashboards.
2. Diagnostic Analytics:
   Diagnostic analytics focuses on understanding why something happened in the past. It involves digging deeper into data to identify the root causes of specific events or behaviors. Diagnostic analytics helps businesses understand the factors that influence outcomes. It answers the question "Why did it happen?" and is crucial for problem-solving and optimization.
3. Predictive Analytics:
   Predictive analytics uses statistical algorithms and machine learning techniques to identify the likelihood of future outcomes based on historical data. It analyzes patterns and trends to make predictions about future events. Predictive analytics helps businesses forecast trends, behavior, and events, allowing them to make proactive decisions. It answers the question "What is likely to happen in the future?"
4. Prescriptive Analytics:
   Prescriptive analytics goes a step further by recommending actions to influence desired outcomes based on predictive models. It not only predicts future outcomes but also suggests the best course of action to achieve specific goals. Prescriptive analytics provides actionable insights, helping businesses make data-driven decisions. It answers the question "What should be done to achieve a desired outcome?"

Some softwares included are Python, Matlab, R-Statistic, C++, SmartPLS, World Cloud Software.