Obinna Dike, a software engineer with Citi, is one of many in his
field that understands and applies big data analytics. Companies like
Citi turn to engineers like Obinna Dike to integrate big data analytics
into their business practices because it aids them in understanding and
using the data in their systems. Like other technologies, big data
analytics can be broken down into several subcategories. Some of the
primary subcategories include:
- Data Mining — Data mining allows businesses to inspect large volumes of data and to find patterns that appear within it. This information can then facilitate a more in-depth analysis of data, allowing companies to find answers to difficult questions. In short, data mining software sifts through the unnecessary in data to find what is useful for decision-making.
- Data Management — Before data can be analyzed effectively, it needs to be managed and organized. Most, if not all, large organizations have a steady stream of data flowing both in and out. Data management technologies essentially organize all of this data into a master program that helps keep all stakeholders on the same page.
- Hadoop — Hadoop is a popular open-source framework that is able to store large quantities of data and to run applications on hardware clusters. It has become a primary big data technology as a result of its speedy processing of information, and because of its open-source status. To summarize, Hadoop is a free, reliable technology that processes and stores data.
