Big Data Analytics

What is Big Data Analytics?

Big data analytics aims to analyse big data to reveal information — such as hidden patterns, correlations, market trends, and customer preferences — that can help organisations make informed business decisions. In a broader sense, data analytics provides organisations the technology to analyse data sets and gather fresh information. Basic questions on business operations and performance are well answered by Business Intelligence (BI) queries.

Key Big Data Analytics Technologies and Tools

There are different types of tools and technologies used to support big data analytics processes. Technologies and tools used to enable big data analytics include:

• Hadoop — An open source framework for storing and processing big data sets. Large amounts of structured and unstructured data can be handled with Hadoop.
• Predictive Analytics Hardware and Software — Large amounts of complex data can be processed using machine learning and statistical algorithms to make predictions about future event outcomes. Organisations use predictive analytics tools for fraud detection, marketing, risk assessment, and operations.
• Stream Analytics Tools — Used to filter, aggregate, and analyse big data that can be stored in many different formats or platforms.
• Data Warehouse — A repository that stores large amounts of data collected by different sources. Data warehouses store data using predefined schemas for efficient querying and analysis.