Cloud platforms and other cloud-based technology dominate the world today as they enable organizations to easily collect and store valuable data that are related to clients, products/services as well as employees. These pieces of data can be considered as treasures because they house valuable information related to commerce, statistics and even trends, among others.  However, there can be big challenges in storing and saving them. This is because the amount of data is massive and manual means of storage such as in documents as well as in computer systems won't have enough space.

A data warehouse (DW) can be defined as an assembling of corporate information along with data that is derived from operational systems as well as from external sources. There is a clear line of difference between a data warehouse and a database. Data warehouses support business decisions by enabling data consolidation, analysis and reports at different aggregate levels. However, data warehousing is not meant to support regular reporting needs of a business and/or organization.

Databases and data warehouses are systems that store data but serve very different purposes. A database stores real-time information about a specific portion or department of a company. Databases help process the daily transactions of a company which could include records of daily sales, details of cash transactions, employee attendance, and more. They handle a massive volume of simple queries very quickly. 

A data warehouse is a central repository of information that can be analyzed to make more informed decisions. This concept can be used for any public, private and even nonprofit organization. That is, for storing all data of a business in a single place instead of using multiple systems or paper files.  Data warehousing is the process of constructing and using a data warehouse. This involves data cleaning, data integration and data consolidations.

There have been multiple enhancements along with the addition of new capabilities to the concept of data warehousing and analytics in the past few years.However, data warehousing technologies are still limited with difficulties of implementing and utilizing traditional data warehouses. That is data warehouses are used to absorb, model as well as store data through an Extract, Transform and Load process (ETL). Cost elements and complex technologies are a couple of barriers that prevent further adaption of data warehousing development. SGS Technologie is a professional big data service.

Data is the new king for all business along with multiple industries. SGS Technologie recognizes this as we are a leading big data analytics and data engineering company in Florida. Our team of SMEs are proficient, have good conflict-resolution skills in analyzing data sources Master Data Management, and have good knowledge in application development.  In this post, we are giving an accurate outline of what Master Data Management (MDM) and its difference from Data Warehousing.

This term may sound familiar, but what is really known about data warehousing? Data warehousing refers to the capture of data from diverse sources for useful analysis and access into a database. In simple words, data warehousing solutions collect information from different sources in the internet and store them in a personalised database. These pieces of data can be used anytime to analyse customers’ behaviour, browsing habits, and digital market trends.

This is the era of Big Data and Data Analytics. Yet these massive amounts of information need to be stored and organized accurately for easy access at any time. Data Warehouses are the perfect solution for this. A Data Warehouse is a digital collection of corporate information and data derived from operational systems as well as external data sources. That is, it is a server application which houses all forms of big data and keeps the information secure for future access.

This is a relatively new concept though a lot has been spoken and a lot has been implemented using it.  For a preview, a data warehouse (DW) is a collection of corporate information and data derived from operational systems as well as external data sources. It is different from a database. The purposes of data warehouses are to support business decisions by allowing data consolidation, analysis and reporting at different aggregate levels.