BIG DATA ANALYTICS
Big Data Analytics At The Heart of Business Strategies
Big Data analysis is the combined process of collecting, organizing and analyzing large volumes of data. The ultimate goal of this data analysis is to draw strategic information or models on which companies are going to make their decisions.
Such data analysis is very promising because it helps companies better understand the information in their data warehouses, whether structured or not. Analysis of these data also helps to clearly identify those that are important and play a decisive role in the decisions of leaders. Analysts in charge of this activity have a role whose importance grows as these data are more and more needed within companies.
Data Analysis Requires a Performance Environment
To work on large volumes of data, analytics requires a performance environment with machines and software tools dedicated to predictive analysis, and upstream, to data mining, text mining, organizing and optimizing data, etc. These tools previously used separately have been increasingly integrated into single dedicated environments, making possible the processing of large enterprise data volumes. Predictive analytics on these data will help identify trends and models that the company are always in need of in order to make better decisions.
In order for the analysis to be relevant, it should address a number of challenges. The first two challenges are the large data sets associated with the heterogeneity of data available in different formats within the company. We must therefore have the necessary platforms to integrate these large data, regardless of their formats.
Another challenge is to overcome the inevitable silos in which are confined business data in a company that for example has many subsidiaries, services and systems. We must therefore strive to “flatten the data” and find the different links between them so as to establish a global, coherent and interconnected data set.
Growing Use of Big Data
Technologies are increasingly contributing to shape companies, eliminating data silos and improving data analysis. Commpanies can detect an emerging trend on a market and anticipate a strong demand for a certain type of product (analysis of messages on social networks and forums, for example). These technologies can help government agencies, for example, to prevent and fight against the risk of epidemics, fire, theft, or against the development of a disease by further analysis of the genome of a person, etc..
Benefits of Predictive Analytics
Businesses are hungry for information that make sense for their business and can give them safe guidance for the months and years ahead. Ability to anticipate the future with great reliability, this is a question to which all companies try to answer, and more and more nowadays with the help of big data. Therefore they tend to adopt the best environments (machines, software and specific solutions) to ensure their data further analysis and help them increase their sales, improve the efficiency of their internal processes, and more generally, to reduce risks associated with the uncertainty of their markets.
See also: Definition