Corporate DataWarehouse: More than a desire, a need.

Jan 11, 2023

Nowadays, companies generate an enormous amount of data that, when well used, is a fundamental asset because it allows them to make better business decisions and differentiate themselves from the competition. Therefore, many companies decide to integrate their data into a single repository and automate the organization’s data flow, from the data in transactional systems to the visualization of information in management dashboards. This is how they dive into data analytics, business intelligence tools, machine learning, among other projects, but without a solid understanding of what data can do for their organization and without a strategic approach to such efforts. This ends up causing more problems than the benefits they bring.

One such case is the implementation of the Corporate DataWarehouse, a term that data experts often refer to in their daily practices. In this article, we will start with some key concepts to understand what is a DataWarehouse, also known as a data warehouse, and which has become the most solid, robust and scalable tool in any business intelligence strategy.

 

Content

  • Let’s start with the basics: What is a DataWarehouse?
  • Understanding data warehousing
  • Case Studies: Transactional Databases vs DataWarehouse
  • Why does your company need a data warehouse?
  • How can bintelligenz help you implement efficient data warehousing in your company?

 

Let’s start with the basics: What is a DataWarehouse?

A DataWarehouse is a central storage system for business data. Companies use data warehouses to have a stable and persistent source of information to support their decisions.

In other words, a DataWarehouse is a centralized data repository that draws from a wide range of sources inside and outside the enterprise. It is a technology that combines data from single or multiple sources to provide a unified view to analysts and business users.

It is also important to understand the difference between a transactional database and a data warehouse, as these terms are often confused. Later on, we will see some practical use cases to understand this difference.

Understanding data warehousing

Data warehousing can be defined as the process of collecting, cleansing and transforming and storing data from various sources and managing it to provide valuable business information.

Data analytics is used to provide deeper insight into an organization’s performance by comparing combined data from various sources. A data warehouse allows you to run queries and analysis on historical data obtained from transactional systems.

The data that is placed in the warehouse does not change or modify because the incidents that have occurred in the past are analyzed from there, making it possible to detect changes over time. The main objective of data storage is that the data remains secure, reliable, stable and easily usable.

Case studies: Transactional vs. transactional databases. DataWarehouse

As mentioned above, in the business world there is often confusion between transactional databases, also known as OLTP (On-Line Transaction Processing) and a DataWarehouse or OLAP (On-Line Analytical Processing) database. Let us consider some use cases to clarify both concepts.

OLTP databases are designed to support the operations of enterprise systems; their function is to record simple daily transaction data, such as:

  • Visualization of tons processed per day by a machine.
  • Recording of a patient’s data so that hospital personnel can
  • Logging of hours worked in a workspace.
  • Recording of the daily invoicing operations of a company.

In contrast, OLAP databases are designed to support more sophisticated activities, such as:

  • High-level reporting and analysis for smart business decisions
  • Extract data for present or future needs
  • Analyzing large volumes of data for analytical purposes
  • Analyzing customer behaviors to improve sales and marketing strategies
  • Improving processes and interdepartmental collaboration
  • Obtain useful and unique information, either through reports, ad hoc queries, or automated decision making.

All these examples require massive and complex processing of large volumes of data.

 

Why does your company need a data warehouse?

Consider the following hypothetical, but unfortunately, very common situation in the real world: company XY has a large amount of data, but it is difficult to access it. It takes them a long time to generate reports and end users do not have confidence in the results; perhaps end-of-quarter reports do not align with reality or do not include information from a process or business area. All these data management issues increase friction between different areas of the company.

But situations don’t have to be that way. Let us now consider an opposite scenario: AZ Company has implemented a Corporate DataWarehouse and all areas know that they can access the data accurately and easily when needed. Thus, users will access automatically generated reports and, when their interest is piqued, they will eventually start asking for more. They will realize how easy it is to get useful data from the company or department and start conducting experiments to improve operations, increase sales and save money.

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How can bintelligenz help you implement efficient data warehousing in your company?

Organizations with a well-thought-out data warehousing strategy can plan and stay ahead of their less data-savvy competitors, from product development, marketing, pricing, production processes and historical analysis, to forecasting, employee organization and customer satisfaction.

The bintelligenz solution includes a corporate DataWarehouse that is accessible and simple to use, but with the security, robustness and scalability of an Enterprise-grade product, to make adopting a data-driven culture possible.

No more jumping from Excel file to Excel file to find the right information about a customer or any area of your business. With bintelligenz you will have peace of mind knowing that you can access your business data in seconds, reliably and all centralized in one place. The benefits are many, and the disadvantages are practically nonexistent.

  • Visualize the main KPIs of each area of your business
  • Share updated information with your work teams
  • Discover hidden patterns in your data
  • Improve the decision making process with actionable information, automatically and periodically updated.
  • Operate with a reliable and unified source, reducing disagreements in the organization.

Take advantage of our solution and create an agile data ecosystem today. Contact us or try a demo of our solution here!

Bintelligenz, the only business intelligence solution on the market that is:
✔ All-in-one: bintelligenz covers all processes of a comprehensive BI solution:

  • Data Scoping: understanding existing data and its origin
    Data Integration: validate and transform your data into an integrated model of your organization’s processes.
  • DataWarehouse: enterprise cloud data warehouse with built-in security
  • Data Visualization: world-class visualization tool
  • Data Use: more than 150 pre-assembled dashboards with metrics and KPIs about your business.

✔ No-code: none of the processes require you to program a single line of code; you just need to know your current transactional systems.

✔ Economical: most economical BI solution on the market. Subscription scheme without the need for additional licenses or additional technical staff.

✔ Fast implementation: in as little as 1 month.

✔ With guaranteed success: with our accompanied on-boarding process we guarantee that you will have a complete BI solution for your organization.

 

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