Business Intelligence

Business intelligence (BI) helps businesses analyze current and historical data by combining data mining, business analytics, data visualization, data tools, and best practices to rapidly uncover valuable insights to allow businesses to make strategic data-driven decisions. Business intelligence will make it possible to write a story of your data in a visual format so that you can have a more comprehensive view of them. Doing so will help you drastically increase efficiencies and dynamically adapt to the market trends. At Nordensol we will provide you with all the training and tools to empower your organization to unleash its full potential. From data extraction to decision making we have you covered. We have broken down the process into the following 4 phases:

THE PROCESS

Phase 1: Gather Data from all available sources

During this phase, your data of various formats and sources are automatically extracted, transformed, and loaded into a centralized database to be easily accessed and queried from BI software.


Phase 2: Detect trends and irregularities

Automatically and rapidly analyzing data from the centralized database using tools techniques such as pattern recognition to unveil insights into the current state of affairs of the organization. We will use BI tools for descriptive, statistical, exploratory, and predictive actions to make recommendations and critical predictions.


Phase 3: Data visualization to show reports

The use of interactive maps, graphs, charts, dashboards in reporting allows the user to have an overhead insight into their data. This approach of data visualizations makes it easier for the user to discover pertinent information about their business.


Phase 4: Take action on insights in real-time

Business Intelligence is used to reduce inefficiencies, adjust to market change, resolve customer problems and resolve supply issues by enabling real-time acclimatization and long-term strategic adjustment. Examining past and current data in context with business activities gives the users the aptness to rapid shifts from insights to actions.

These processes include:

  • Data mining: Using databases, statistics, and machine learning to uncover trends in large datasets.

  • Reporting: Sharing data analysis to stakeholders so they can draw conclusions and make decisions.

  • Performance metrics and benchmarking: Comparing current performance data to historical data to track performance against goals, typically using customized dashboards.

  • Descriptive analytics: Using preliminary data analysis to find out what happened.

  • Querying: Asking the data-specific questions, BI pulling the answers from the datasets.

  • Statistical analysis: Taking the results from descriptive analytics and further exploring the data using statistics such as how this trend happened and why.

  • Data visualization: Turning data analysis into visual representations such as charts, graphs, and histograms to more easily consume data.

  • Visual analysis: Exploring data through visual storytelling to communicate insights on the fly and stay in the flow of analysis.

  • Data preparation: Compiling multiple data sources, identifying the dimensions and measurements, preparing it for data analysis.

ADVANTAGES AND APPLICATIONS

DATA ANALYSIS

Analyze customer behavior and identify ways to increase your revenue.

  • Discover issues

  • pinpoint market trends

  • Optimize operations

  • Predict success

  • Track performance

  • Compare data with competitors

ADVANTAGES

1. Increase productivity

Easily visualize and share your data amongst your team

2. Improve clearness

Improve visibility to easily detect any irregularities

3. Fix Accountability

BI tools define accountability within the organization for set target

4. It gives an overhead view

Dashboard and scoreboard give the decision-makers an overall view of all data analysis and reports

5. It simplifies business rules:

Makes all business rules simple and provide automated data analytics through various type of techniques.

6. It allows user-friendly analytics.

Provide user-friendly interface to enable anyone in the organization to receive and prepare data without delays