Data Management

Greater flexibility in the big data solution that we provide to your “big data” sector

Big Data

Big data is a field that treats ways to analyze, systematically extract information from, or otherwise deal with data sets that are too large or complex to be dealt with by traditional data-processing application software.

Analysis of data sets can find new correlations to “spot business trends, prevent diseases, combat crime and so on. Scientists, business executives, practitioners of medicine, advertising and governments alike regularly meet difficulties with large data-sets in areas including Internet searches, fintech, urban informatics, and business informatics.

DIDIT Big Data Solution provides the flexibility and ease of extracting the data your business or government sector requires.

Data Mining

Data mining is a process that used by DIDIT Data Management department used to turn raw data into useful information. By using software to look for patterns in large batches of data, businesses can learn more about their customers to develop more effective marketing strategies, increase sales and decrease costs. Data mining depends on effective data collection, warehousing, and computer processing.

The actual data mining task is the semi-automatic or automatic analysis of large quantities of data to extract previously unknown, interesting patterns such as groups of data records (cluster analysis), unusual records (anomaly detection), and dependencies (association rule mining, sequential pattern mining).

Big Data Security

There is an ever-increasing number of people, devices and sensors that generate, communicate and share data via the global internet.

Analysing this data can help organizations to develop new products, improve their efficiency and effectiveness, as well as to make better decisions. This report describes the challenges of using Big Data in ways that are secure, compliant and ethical and how meeting these challenges requires a data-centric approach to security.

DIDIT is specialized in building and securing the big data business sector