How does data warehouse modernization impact data quality and integration?
Posted: Tue Jan 21, 2025 3:52 am
Data warehouse modernization is inevitable if you want to have reliable, secure, quality and 100% integrated data. Discover its impact in this article.
Main problems of an old data warehouse.
Integrating data, people and technology are three equally important factors in the use, management and analysis of information that lead to intelligent decision making in modern companies.
Modernizing the data warehouse allows for the addition of innovative technological solutions that adapt to current data and analytics demands.
Achieving data warehouse modernization takes time and expertise, especially for organizations that still rely on legacy data centers that have become obsolete.
Let's look at the main problems these companies have.
Data Ingestion
The first problem is related to the data ingestion format that afghanistan phone number lead many older solutions offer. The loading and transfer of information tends to be inflexible and connectivity is limited. In addition, there is no real-time data incorporation or updating, which limits the transformation of data for analysis and rapid delivery of information.
Data transformation, data center creation and lifecycle automation
The second problem that traditional data warehouse users encounter is that they spend many hours manually writing SQL scripts to restructure the ingested data, even more so if they want to follow a data vault design or dimensional modeling methodology.
The lack of automation at this point is really a major limitation to having fast and correct data.
Lack of support for unstructured and semi-structured data
Traditional data warehouses are primarily designed for structured data. Modernization can involve incorporating unstructured or semi-structured data, such as social media data, web application logs, and documents, for a more complete view of the organization's data.
High costs for equipment and its maintenance
Modernizing your data warehouse can help reduce operational and maintenance costs, especially if you migrate to a cloud-based solution that eliminates the need to maintain expensive physical infrastructure.
Becoming a data-driven organization that aims to modernize the data warehouse to achieve data quality and data integration involves overcoming many challenges that fall within traditional and inefficient business actions and processes.
Why should your company have a modern data warehouse?
Traditional data warehouses are unable to keep up with the accelerated pace of demand brought on by big data volumes, processing jobs, and real-time data analytics.
Modernizing your data warehouse is essential to staying relevant and responsive in an ever-changing business environment. This enables organizations to make the most of their data and make strategic decisions based on up-to-date and accurate information.
Thanks to modernization, organizations can adapt to different scenarios and changing market situations that arise throughout their life because these are solutions that apply intelligent technology that is constantly updated. AI , Big Data, automation and other innovations necessarily require data warehouse modernization .
Qlik offers market-leading data warehouse automation solutions and recently added Talend capabilities to the Qlik Data Integration family.
This merger enables modern businesses to access, transform, analyze and make decisions through trusted information. The goal is to achieve an intelligent union of data integration, quality and analytics.
Implementing a data warehouse is truly transformative for many organizations, but the mere existence of the warehouse is not enough.
Main problems of an old data warehouse.
Integrating data, people and technology are three equally important factors in the use, management and analysis of information that lead to intelligent decision making in modern companies.
Modernizing the data warehouse allows for the addition of innovative technological solutions that adapt to current data and analytics demands.
Achieving data warehouse modernization takes time and expertise, especially for organizations that still rely on legacy data centers that have become obsolete.
Let's look at the main problems these companies have.
Data Ingestion
The first problem is related to the data ingestion format that afghanistan phone number lead many older solutions offer. The loading and transfer of information tends to be inflexible and connectivity is limited. In addition, there is no real-time data incorporation or updating, which limits the transformation of data for analysis and rapid delivery of information.
Data transformation, data center creation and lifecycle automation
The second problem that traditional data warehouse users encounter is that they spend many hours manually writing SQL scripts to restructure the ingested data, even more so if they want to follow a data vault design or dimensional modeling methodology.
The lack of automation at this point is really a major limitation to having fast and correct data.
Lack of support for unstructured and semi-structured data
Traditional data warehouses are primarily designed for structured data. Modernization can involve incorporating unstructured or semi-structured data, such as social media data, web application logs, and documents, for a more complete view of the organization's data.
High costs for equipment and its maintenance
Modernizing your data warehouse can help reduce operational and maintenance costs, especially if you migrate to a cloud-based solution that eliminates the need to maintain expensive physical infrastructure.
Becoming a data-driven organization that aims to modernize the data warehouse to achieve data quality and data integration involves overcoming many challenges that fall within traditional and inefficient business actions and processes.
Why should your company have a modern data warehouse?
Traditional data warehouses are unable to keep up with the accelerated pace of demand brought on by big data volumes, processing jobs, and real-time data analytics.
Modernizing your data warehouse is essential to staying relevant and responsive in an ever-changing business environment. This enables organizations to make the most of their data and make strategic decisions based on up-to-date and accurate information.
Thanks to modernization, organizations can adapt to different scenarios and changing market situations that arise throughout their life because these are solutions that apply intelligent technology that is constantly updated. AI , Big Data, automation and other innovations necessarily require data warehouse modernization .
Qlik offers market-leading data warehouse automation solutions and recently added Talend capabilities to the Qlik Data Integration family.
This merger enables modern businesses to access, transform, analyze and make decisions through trusted information. The goal is to achieve an intelligent union of data integration, quality and analytics.
Implementing a data warehouse is truly transformative for many organizations, but the mere existence of the warehouse is not enough.