As tech progresses, the importance of data tracking is on the rise. The global surge in data results in almost 2.5 quintillion bytes; without proper organization, this data proves ineffective. Collecting useful market data is a key element in maintaining business consistency. Optimal decision-making for a company requires properly managing vast raw data.
This is possible using the right data analytic tool and a skilled data analyst. A business can improve decision-making by using a big data analytics framework. They can discover patterns, customer preferences, and concealed market trends within the data. Data analysts play a vital role in aiding firms to refine their decision-making processes. They can use software and a big data analytics structure tailored for large-scale data analysis.
- APACHE Cassandra enables the retrieval of large data sets through its distributed database with a no-SQL engine.
- Apache Spark allows large-scale data processing and various tasks across multiple computers.
- Qubole uses open-source tech for big data analytics. It fetches data from a value chain through ad-hoc analysis in ML.
- MongoDB is a document-oriented (NoSQL) database. It is an open-source platform for the structured storage of large amounts of information.
- Storm is a robust and user-friendly tool small companies use for big data analytics.
- Rapid Miner automates the design of data analytics workflows using visual tools.
The process of obtaining, managing, analyzing, and identifying patterns in large data sets is known as Big Data analytics. It helps companies make informed decisions.
Analysts use various tools for data analysis, purification, mining, storage, and big data management. They can improve their decision-making processes using various big data analytics tools.