BI and Big Data, a Strategic Alliance to Boost Your Business
Posted: Tue Jan 21, 2025 10:01 am
Combining BI and Big Data enables powerful analysis of a large amount of data that provides a key competitive advantage: transforming any type of data (volume, form, location) into high value-added information for each sector of the company.
However, it is necessary to know how to exploit this raw material so that it becomes the greatest capital of an organization: the relevant knowledge of the business.
The BI and Big Data alliance allows, among other things, to measure consumer sentiment, optimize supply chains and detect fraud.
QlikView offers two Big Data management models, QlikView In-Memory and Direct Discovery. Let's find out how both deliver an excellent user experience.
BI and Big Data: When Unity is Strength
Today, there is a strong tendency among organizations to estonia phone number lead complement the use of BI with Big Data functionality. This combination aims to facilitate decision-making by users in the face of the constant increase in data to be analyzed.
How do they complement each other?
BI is a system that analyzes your organization's structured data to help you make better decisions with one goal: boosting your business results .
Big Data is a set of technology, architecture, and processes that allows for the rapid capture, processing, and analysis of large volumes of data and quantities of heterogeneous content that are constantly evolving.
Big Data adds to your BI solution the essential power to extract relevant information in a simple and accessible way for everyone.
To know whether it is possible to make Big Data definitively useful in decision-making, it is essential to know what processes are carried out by executives.
The BI and Big Data Analysis Process
The Big Data analysis process follows a path that develops in four stages;
1- Access to raw data.
The first stage begins with access to “fresh” data. This is information of high volume, velocity, and variety, which is generally poorly structured. (For example, transaction data, system data, or cloud data, among others.)
2- First Round of Processing.
The files to be stored are copied to a Hadoop cluster, a portable and simple-to-use file system designed to run on hardware. This tool allows the manipulation of raw data in order to facilitate user interpretation.
3- More Processing.
Organizations also have their own company data that needs to be analyzed using a warehouse called EDW. Unlike Hadoop, it is a structured system that does not work with raw data, which makes it easier for users to consult.
4- Analysis.
This is the final stage. The analytics tool that best fits a business user's needs should flexibly integrate data from multiple sources and make no assumptions about where the data comes from and how it is organized.
In short, this process begins with a global analysis of data, the organized structuring up to the final decision making. Understanding this process allows you to understand the advantages of implementing Big Data in your organization.
Self-management as an alternative
Today, IT professionals and business leaders have begun to understand the advantages that Big Data applications provide, as they consider it a favorable means for self-management.
Since its emergence, Big Data has focused on the analysis of large volumes of data through complex calculations.
For this process to take place, it is necessary to hire a staff in charge of programming the algorithms with the necessary time to do so, and it requires making massive investments in software and infrastructure.
Faced with this difficulty presented by this algorithmic model, a novel alternative was developed: allowing users to access the data on their own.
However, it is necessary to know how to exploit this raw material so that it becomes the greatest capital of an organization: the relevant knowledge of the business.
The BI and Big Data alliance allows, among other things, to measure consumer sentiment, optimize supply chains and detect fraud.
QlikView offers two Big Data management models, QlikView In-Memory and Direct Discovery. Let's find out how both deliver an excellent user experience.
BI and Big Data: When Unity is Strength
Today, there is a strong tendency among organizations to estonia phone number lead complement the use of BI with Big Data functionality. This combination aims to facilitate decision-making by users in the face of the constant increase in data to be analyzed.
How do they complement each other?
BI is a system that analyzes your organization's structured data to help you make better decisions with one goal: boosting your business results .
Big Data is a set of technology, architecture, and processes that allows for the rapid capture, processing, and analysis of large volumes of data and quantities of heterogeneous content that are constantly evolving.
Big Data adds to your BI solution the essential power to extract relevant information in a simple and accessible way for everyone.
To know whether it is possible to make Big Data definitively useful in decision-making, it is essential to know what processes are carried out by executives.
The BI and Big Data Analysis Process
The Big Data analysis process follows a path that develops in four stages;
1- Access to raw data.
The first stage begins with access to “fresh” data. This is information of high volume, velocity, and variety, which is generally poorly structured. (For example, transaction data, system data, or cloud data, among others.)
2- First Round of Processing.
The files to be stored are copied to a Hadoop cluster, a portable and simple-to-use file system designed to run on hardware. This tool allows the manipulation of raw data in order to facilitate user interpretation.
3- More Processing.
Organizations also have their own company data that needs to be analyzed using a warehouse called EDW. Unlike Hadoop, it is a structured system that does not work with raw data, which makes it easier for users to consult.
4- Analysis.
This is the final stage. The analytics tool that best fits a business user's needs should flexibly integrate data from multiple sources and make no assumptions about where the data comes from and how it is organized.
In short, this process begins with a global analysis of data, the organized structuring up to the final decision making. Understanding this process allows you to understand the advantages of implementing Big Data in your organization.
Self-management as an alternative
Today, IT professionals and business leaders have begun to understand the advantages that Big Data applications provide, as they consider it a favorable means for self-management.
Since its emergence, Big Data has focused on the analysis of large volumes of data through complex calculations.
For this process to take place, it is necessary to hire a staff in charge of programming the algorithms with the necessary time to do so, and it requires making massive investments in software and infrastructure.
Faced with this difficulty presented by this algorithmic model, a novel alternative was developed: allowing users to access the data on their own.