About Big Data.

Big-Data

What started the massive data revolution?

Business problems:

  1. Large amount of accumulated data made it impossible to process it on a single computer.
  2. Heterogeneity of data. Need to insert, consult and process data in different structures.
  3. Need to quickly process the data.

Definition:

In 2001, analyst Doug Laney’s GOAL Group (now Gartner) used to define the concept of Big Data as:

“The set of techniques and technologies for data processing, in high-volume environments, a variety of origins and in which response speed is critical. “

When to apply a Business Intelligence (BI) solution based on Big Data?

If there is a large volume of data, high speed of data generation or need to treat all types of data.

Can Big Data be applied in any BI project?

Big data can be used in any scenario to analyse information obtained from different information systems. Must consider the increase in complexity and cost compared to a traditional BI solution.

Differences: Traditional BI and Big Data.

Nature of the data:

  • Volume, Variety and Speed.

Granularity:

  • Traditional BI data stored in the DW at its minimum
    Granularity.
  • Big Data stored in the DW are derived or filtered.

Technology:

  • Hadoop + NoSQL database.
  • DBMS + BI tool.

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