Webinar Held: "The Proliferation and Complexity of DWH/BI: Why Isn't the Vast Amount of Accumulated Data Utilized Company-Wide?"
Majisemi Co., Ltd. will hold a webinar on "Data Virtualization x Lakehouse" to address the challenges of DWH/BI proliferation and underutilized data. It will explain how to realize a next-generation data infrastructure using Databricks and Denodo.
📋 Article Processing Timeline
- 📰 Published: April 22, 2026 at 18:00
- 🔍 Collected: April 23, 2026 at 00:02 (6h 2m after Published)
- 🤖 AI Analyzed: April 23, 2026 at 06:59 (6h 57m after Collected)
Click here for details and registration.
■ Increasing DWH/BI and Fragmented Data
With the acceleration of DX and the growing demand for data utilization led by individual departments, DWH and BI tools have been introduced in each department, leading to a diverse array of data infrastructures within companies. The spread of cloud computing has made data accumulation easier, and data lakes and various data marts are being built one after another.
However, without a design that considers overall optimization, systems have continued to increase in a piecemeal fashion, resulting in a proliferation and complexity of data infrastructures. Challenges such as "I don't know where what data is" and "The numbers differ by department even for the same metric" have become apparent.
■ The Challenge of Accumulated Data Not Being Utilized on Site
Originally, DWH and BI are mechanisms to connect scattered data within a company, quickly grasp necessary information, and link it to decision-making and on-site actions. However, in reality, data is often dispersed across departments and systems, and many companies are unable to utilize it uniformly across the entire organization.
For example, you might encounter situations such as:
・Different DWHs and business systems exist for each department, and necessary data is dispersed.
・Even for the same metric, the reference source and definition differ, leading to inconsistent numbers.
・When trying to view data across systems, extraction, processing, and reconciliation work occurs every time.
As a result, even if data is accumulated, it often falls into a situation where it cannot be fully utilized for comprehensive analysis or rapid decision-making. On the other hand, attempting to forcibly integrate all dispersed data can sometimes increase costs and operational burden, leading to unrealistic utilization.
■ How to Realize a Next-Generation Data Infrastructure by Organizing Roles with Data Virtualization x Lakehouse
In this seminar, we will introduce the concept of how to organize the roles of a proliferating and complex DWH/BI environment and realize a company-wide usable data utilization platform, by leveraging Databricks, which enables a lakehouse, and Denodo, which handles data virtualization.
Specifically, we will explain the approach to realizing a company-wide data utilization infrastructure by appropriately choosing between Databricks' lakehouse and Denodo's data virtualization, and selecting between physical data movement and real-time utilization.
Instead of "rebuilding everything," we will introduce a practical solution for building a next-generation data infrastructure by "organizing, leveraging, and connecting," along with concrete examples.
■ Recommended for:
・Those considering reviewing overall optimization due to the proliferation of DWH and BI within their company.
・Those who feel challenged because data is accumulated but not being utilized on site.
・Those specifically considering the introduction of lakehouse or data virtualization.
・IT/data department personnel who want to redraw their medium-to-long-term data infrastructure strategy.
■ Hosted/Co-hosted by
NSW Co., Ltd.
■ Cooperated by
Denodo Technologies Co., Ltd.
Open Source Utilization Research Institute Co., Ltd.
Majisemi Co., Ltd.
Click here for details and registration.
Majisemi will continue to hold webinars that are "useful for participants" in the future.
Past seminar materials and other currently recruiting seminars can be viewed here.
Majisemi Co., Ltd.
3F Shiodome Building, 1-2-20 Kaigan, Minato-ku, Tokyo 105-0022
Inquiries: https://majisemi.com/service/contact/
Keywords:
■ Increasing DWH/BI and Fragmented Data
With the acceleration of DX and the growing demand for data utilization led by individual departments, DWH and BI tools have been introduced in each department, leading to a diverse array of data infrastructures within companies. The spread of cloud computing has made data accumulation easier, and data lakes and various data marts are being built one after another.
However, without a design that considers overall optimization, systems have continued to increase in a piecemeal fashion, resulting in a proliferation and complexity of data infrastructures. Challenges such as "I don't know where what data is" and "The numbers differ by department even for the same metric" have become apparent.
■ The Challenge of Accumulated Data Not Being Utilized on Site
Originally, DWH and BI are mechanisms to connect scattered data within a company, quickly grasp necessary information, and link it to decision-making and on-site actions. However, in reality, data is often dispersed across departments and systems, and many companies are unable to utilize it uniformly across the entire organization.
For example, you might encounter situations such as:
・Different DWHs and business systems exist for each department, and necessary data is dispersed.
・Even for the same metric, the reference source and definition differ, leading to inconsistent numbers.
・When trying to view data across systems, extraction, processing, and reconciliation work occurs every time.
As a result, even if data is accumulated, it often falls into a situation where it cannot be fully utilized for comprehensive analysis or rapid decision-making. On the other hand, attempting to forcibly integrate all dispersed data can sometimes increase costs and operational burden, leading to unrealistic utilization.
■ How to Realize a Next-Generation Data Infrastructure by Organizing Roles with Data Virtualization x Lakehouse
In this seminar, we will introduce the concept of how to organize the roles of a proliferating and complex DWH/BI environment and realize a company-wide usable data utilization platform, by leveraging Databricks, which enables a lakehouse, and Denodo, which handles data virtualization.
Specifically, we will explain the approach to realizing a company-wide data utilization infrastructure by appropriately choosing between Databricks' lakehouse and Denodo's data virtualization, and selecting between physical data movement and real-time utilization.
Instead of "rebuilding everything," we will introduce a practical solution for building a next-generation data infrastructure by "organizing, leveraging, and connecting," along with concrete examples.
■ Recommended for:
・Those considering reviewing overall optimization due to the proliferation of DWH and BI within their company.
・Those who feel challenged because data is accumulated but not being utilized on site.
・Those specifically considering the introduction of lakehouse or data virtualization.
・IT/data department personnel who want to redraw their medium-to-long-term data infrastructure strategy.
■ Hosted/Co-hosted by
NSW Co., Ltd.
■ Cooperated by
Denodo Technologies Co., Ltd.
Open Source Utilization Research Institute Co., Ltd.
Majisemi Co., Ltd.
Click here for details and registration.
Majisemi will continue to hold webinars that are "useful for participants" in the future.
Past seminar materials and other currently recruiting seminars can be viewed here.
Majisemi Co., Ltd.
3F Shiodome Building, 1-2-20 Kaigan, Minato-ku, Tokyo 105-0022
Inquiries: https://majisemi.com/service/contact/
Keywords: