Is it possible to be Data Driven with an old data warehouse?
Posted: Tue Jan 21, 2025 3:52 am
An old data warehouse may have limitations when it comes to extracting information in real time and in an agile manner. However, this is not an impediment to becoming a Data Driven company.
Discover how to face challenges and overcome them effectively.
The challenges of becoming a data-driven organization
Becoming a Data Driven organization involves overcoming many challenges that fall within traditional and inefficient business actions and processes.
These challenges are linked to incorrect data detection due to data coming from unknown and unsynchronized sources. They are also related to the use of technology that is difficult for members of the organization to access.
Another challenge is inadequate management and connection of metadata, especially in companies with legacy data systems whose migration is complex and may even be impossible.
At the same time, the lack of democratization of data also afghanistan phone number lead becomes a problem since, when intelligent decisions are left in the hands of a few people, a large part of the collaborators do not come to understand the value of the information and do not use it.
A traditional data warehouse cannot keep pace with the demand for rapidly growing data volumes, processing jobs, and real-time data analytics use cases.
However, despite having an old data warehouse, companies can invest in innovation by adapting their capabilities to the tools they have and incorporating other solutions that collaborate in the use and enhance the use of data.
In light of this, integrating data, people and technology becomes central, since these three factors are equally important in the use, management and analysis of information that leads to intelligent decision-making.
So, can you be Data Driven with an old data warehouse?
Companies with a legacy data warehouse can become data-driven organizations as long as they have an internal culture focused on obtaining valuable knowledge from stored data.
Although the complexity to achieve this may be greater than in agile and modern infrastructures, a well-managed and managed data warehouse can generate relevant information to be used.
It is important to consider some points in this regard:
Ensure that stored data is accurate, complete and well organized . The quality of information is much more important when storage tools are old, so it is essential to pay attention to this point.
Provide full access and availability of stored data to enable information analysis. This can be achieved by complementing ELT solutions that drive extraction, transformation and loading.
Having processing capacity in accordance with the capacity and technological limitations of the old data warehouse . Despite its age, it is possible to perform analysis and obtain knowledge in real time, which will logically take more time and effort.
Drive integration using other data sources to achieve a complete and up-to-date view of information. This may involve using additional tools to extract, transform and combine data from different sources.
Despite potential limitations, such as increased slowness and complexity in obtaining data, a data-driven approach is possible with a legacy data warehouse.
Discover how to face challenges and overcome them effectively.
The challenges of becoming a data-driven organization
Becoming a Data Driven organization involves overcoming many challenges that fall within traditional and inefficient business actions and processes.
These challenges are linked to incorrect data detection due to data coming from unknown and unsynchronized sources. They are also related to the use of technology that is difficult for members of the organization to access.
Another challenge is inadequate management and connection of metadata, especially in companies with legacy data systems whose migration is complex and may even be impossible.
At the same time, the lack of democratization of data also afghanistan phone number lead becomes a problem since, when intelligent decisions are left in the hands of a few people, a large part of the collaborators do not come to understand the value of the information and do not use it.
A traditional data warehouse cannot keep pace with the demand for rapidly growing data volumes, processing jobs, and real-time data analytics use cases.
However, despite having an old data warehouse, companies can invest in innovation by adapting their capabilities to the tools they have and incorporating other solutions that collaborate in the use and enhance the use of data.
In light of this, integrating data, people and technology becomes central, since these three factors are equally important in the use, management and analysis of information that leads to intelligent decision-making.
So, can you be Data Driven with an old data warehouse?
Companies with a legacy data warehouse can become data-driven organizations as long as they have an internal culture focused on obtaining valuable knowledge from stored data.
Although the complexity to achieve this may be greater than in agile and modern infrastructures, a well-managed and managed data warehouse can generate relevant information to be used.
It is important to consider some points in this regard:
Ensure that stored data is accurate, complete and well organized . The quality of information is much more important when storage tools are old, so it is essential to pay attention to this point.
Provide full access and availability of stored data to enable information analysis. This can be achieved by complementing ELT solutions that drive extraction, transformation and loading.
Having processing capacity in accordance with the capacity and technological limitations of the old data warehouse . Despite its age, it is possible to perform analysis and obtain knowledge in real time, which will logically take more time and effort.
Drive integration using other data sources to achieve a complete and up-to-date view of information. This may involve using additional tools to extract, transform and combine data from different sources.
Despite potential limitations, such as increased slowness and complexity in obtaining data, a data-driven approach is possible with a legacy data warehouse.