Data Management vs Data Warehousing

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.

At the same time, Data warehouses can be defined as systems that combine data from different sources within an organization for reporting and analysis. The reports that are created from complex queries within a data warehouse are used to make business decisions. A data warehouse stores historical data about your business so that you can analyze and extract insights from it. It does not store current information, nor is it updated in real-time.

These were the basic definitions. However, SGS Technologie gives a comprehensive description of the concepts of Database Management and Data Warehousing, so that an appropriate decision can be taken on which to choose for your line of operations.

Feature	DATABASE MANAGEMENT	DATA WAREHOUSING
Processing Types	On-Line Analytical Processing (OLAP) is used to swiftly analyze massive volumes of data. This process gives the advantage of analyzing data from different perspectives.	Online Transactional Processing (OLTP) is used to delete, insert, replace, and update large numbers of short online transactions quickly. For example, number of units sold per day or even per hour can be derived.
Optimization	A database is optimized to update (add, modify, or delete) data with maximum speed and efficiency.	Data warehouses can be optimized to speedily execute a few complex queries on large multi-dimensional datasets.
Data Structure	Data in databases are normalized to reduce and eliminate data redundancy, which means databases eliminate storage of same data piece more than once.	Often data is denormalized and contains repeated data for easier access and to perform complex queries.
Data Analysis	A skilled developer or analyst is required to create and execute complex queries on a Data Base Management System (DBSM), which could require massive time and computing resources.	Data warehouses are designed to perform complex analytical queries on large multi-dimensional datasets. There is no need for knowledge of sophisticated DBMS software.
Timeline	Databases manage daily transactions for one aspect or department of a company. Hence, they typically will contain current, rather than historical data about one business process.	Data warehouses are used for analytical purposes and business reporting. They can store historical data by integrating copies of transaction data from disparate sources.
Concurrent Users	Databases support multiple concurrent users because they are updated in real-time to reflect a business’ transactions. However, only one user can modify a piece of data at a time.	Data warehouses support a limited number of concurrent users. A data warehouse is separated from front-end applications.
ACID Compliance	Database transactions are normally executed in an ACID (Atomic, Consistent, Isolated, and Durable) compliant manner. That is, database management systems can function even in the event of errors or power failures.	Data warehouses focus on reading instead of modifying, historical data that is derived from various sources. Hence, ACID compliance is not strictly enforced to a big extent.

This is just an outline of the core differences between database management and data warehousing. There is more that can specifically benefit various components of your business. Reach out to SGS Technologie- an experienced data analytical and DBMS software development company in Florida for further analysis. We are headquartered in Jacksonville and can give a more detailed description over direct meetings, phone calls, and/or emails.

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Data Management and Data Warehousing

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"articleSection" : "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",
"articleBody" : "At the same time, <A href=\"https://www.sgstechnologies.net/solutions/data-warehousing\">Data warehouses</A> can be defined as systems that combine data from different sources within an organization for reporting and analysis. The reports that are created from complex queries within a data warehouse are used to make business decisions. A data warehouse stores historical data about your business so that you can analyze and extract insights from it. It does not store current information, nor is it updated in real-time.\n\nThese were the basic definitions. However, SGS Technologie gives a comprehensive description of the concepts of Database Management and Data Warehousing, so that an appropriate decision can be taken on which to choose for your line of operations.\n\n<TABLE class=\"MsoTableGrid\" style=\"border-collapse:collapse; border:solid windowtext 1.0pt\">\n\t<TBODY>\n\t\t<TR>\n\t\t\t<TD style=\"border:solid windowtext 1.0pt; background:#d9e2f3; width:134.85pt; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"180\">\n\t\t\tFeature\n\t\t\t</TD>\n\t\t\t<TD style=\"border:solid windowtext 1.0pt; background:#d9e2f3; width:166.75pt; border-left:none; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"222\">\n\t\t\tDATABASE MANAGEMENT\n\t\t\t</TD>\n\t\t\t<TD style=\"border:solid windowtext 1.0pt; background:#d9e2f3; width:165.9pt; border-left:none; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"221\">\n\t\t\tDATA WAREHOUSING\n\t\t\t</TD>\n\t\t</TR>\n\t\t<TR>\n\t\t\t<TD style=\"border:solid windowtext 1.0pt; width:134.85pt; border-top:none; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"180\">\n\t\t\tProcessing Types\n\t\t\t</TD>\n\t\t\t<TD style=\"border-bottom:solid windowtext 1.0pt; width:166.75pt; border-top:none; border-left:none; border-right:solid windowtext 1.0pt; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"222\">\n\t\t\tOn-Line Analytical Processing (OLAP) is used to swiftly analyze massive volumes of data. This process gives the advantage of analyzing data from different perspectives.\n\t\t\t</TD>\n\t\t\t<TD style=\"border-bottom:solid windowtext 1.0pt; width:165.9pt; border-top:none; border-left:none; border-right:solid windowtext 1.0pt; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"221\">\n\t\t\tOnline Transactional Processing (OLTP) is used to delete, insert, replace, and update large numbers of short online transactions quickly. For example, number of units sold per day or even per hour can be derived.\n\t\t\t</TD>\n\t\t</TR>\n\t\t<TR>\n\t\t\t<TD style=\"border:solid windowtext 1.0pt; width:134.85pt; border-top:none; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"180\">\n\t\t\tOptimization\n\t\t\t</TD>\n\t\t\t<TD style=\"border-bottom:solid windowtext 1.0pt; width:166.75pt; border-top:none; border-left:none; border-right:solid windowtext 1.0pt; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"222\">\n\t\t\tA database is optimized to update (add, modify, or delete) data with maximum speed and efficiency. \n\t\t\t</TD>\n\t\t\t<TD style=\"border-bottom:solid windowtext 1.0pt; width:165.9pt; border-top:none; border-left:none; border-right:solid windowtext 1.0pt; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"221\">\n\t\t\tData warehouses can be optimized to speedily execute a few complex queries on large multi-dimensional datasets.\n\t\t\t</TD>\n\t\t</TR>\n\t\t<TR>\n\t\t\t<TD style=\"border:solid windowtext 1.0pt; width:134.85pt; border-top:none; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"180\">\n\t\t\tData Structure\n\t\t\t</TD>\n\t\t\t<TD style=\"border-bottom:solid windowtext 1.0pt; width:166.75pt; border-top:none; border-left:none; border-right:solid windowtext 1.0pt; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"222\">\n\t\t\tData in databases are normalized to reduce and eliminate data redundancy, which means databases eliminate storage of same data piece more than once.\n\t\t\t</TD>\n\t\t\t<TD style=\"border-bottom:solid windowtext 1.0pt; width:165.9pt; border-top:none; border-left:none; border-right:solid windowtext 1.0pt; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"221\">\n\t\t\tOften data is denormalized and contains repeated data for easier access and to perform complex queries.\n\t\t\t</TD>\n\t\t</TR>\n\t\t<TR>\n\t\t\t<TD style=\"border:solid windowtext 1.0pt; width:134.85pt; border-top:none; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"180\">\n\t\t\tData Analysis\n\t\t\t</TD>\n\t\t\t<TD style=\"border-bottom:solid windowtext 1.0pt; width:166.75pt; border-top:none; border-left:none; border-right:solid windowtext 1.0pt; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"222\">\n\t\t\tA skilled developer or analyst is required to create and execute complex queries on a Data Base Management System (DBSM), which could require massive time and computing resources.\n\t\t\t</TD>\n\t\t\t<TD style=\"border-bottom:solid windowtext 1.0pt; width:165.9pt; border-top:none; border-left:none; border-right:solid windowtext 1.0pt; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"221\">\n\t\t\tData warehouses are designed to perform complex analytical queries on large multi-dimensional datasets. There is no need for knowledge of sophisticated DBMS software.\n\t\t\t</TD>\n\t\t</TR>\n\t\t<TR>\n\t\t\t<TD style=\"border:solid windowtext 1.0pt; width:134.85pt; border-top:none; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"180\">\n\t\t\tTimeline\n\t\t\t</TD>\n\t\t\t<TD style=\"border-bottom:solid windowtext 1.0pt; width:166.75pt; border-top:none; border-left:none; border-right:solid windowtext 1.0pt; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"222\">\n\t\t\tDatabases manage daily transactions for one aspect or department of a company. Hence, they typically will contain current, rather than historical data about one business process.\n\t\t\t</TD>\n\t\t\t<TD style=\"border-bottom:solid windowtext 1.0pt; width:165.9pt; border-top:none; border-left:none; border-right:solid windowtext 1.0pt; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"221\">\n\t\t\tData warehouses are used for analytical purposes and business reporting. They can store historical data by integrating copies of transaction data from disparate sources.\n\t\t\t</TD>\n\t\t</TR>\n\t\t<TR>\n\t\t\t<TD style=\"border:solid windowtext 1.0pt; width:134.85pt; border-top:none; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"180\">\n\t\t\tConcurrent Users\n\t\t\t</TD>\n\t\t\t<TD style=\"border-bottom:solid windowtext 1.0pt; width:166.75pt; border-top:none; border-left:none; border-right:solid windowtext 1.0pt; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"222\">\n\t\t\tDatabases support multiple concurrent users because they are updated in real-time to reflect a business� transactions. However, only one user can modify a piece of data at a time.\n\t\t\t</TD>\n\t\t\t<TD style=\"border-bottom:solid windowtext 1.0pt; width:165.9pt; border-top:none; border-left:none; border-right:solid windowtext 1.0pt; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"221\">\n\t\t\tData warehouses support a limited number of concurrent users. A data warehouse is separated from front-end applications.\n\t\t\t</TD>\n\t\t</TR>\n\t\t<TR>\n\t\t\t<TD style=\"border:solid windowtext 1.0pt; width:134.85pt; border-top:none; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"180\">\n\t\t\tACID Compliance\n\t\t\t</TD>\n\t\t\t<TD style=\"border-bottom:solid windowtext 1.0pt; width:166.75pt; border-top:none; border-left:none; border-right:solid windowtext 1.0pt; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"222\">\n\t\t\tDatabase transactions are normally executed in an ACID (Atomic, Consistent, Isolated, and Durable) compliant manner. That is, database management systems can function even in the event of errors or power failures.\n\t\t\t</TD>\n\t\t\t<TD style=\"border-bottom:solid windowtext 1.0pt; width:165.9pt; border-top:none; border-left:none; border-right:solid windowtext 1.0pt; padding:0cm 5.4pt 0cm 5.4pt\" valign=\"top\" width=\"221\">\n\t\t\tData warehouses focus on reading instead of modifying, historical data that is derived from various sources. Hence, ACID compliance is not strictly enforced to a big extent.\n\t\t\t</TD>\n\t\t</TR>\n\t</TBODY>\n</TABLE>\n\nThis is just an outline of the core differences between database management and data warehousing. There is more that can specifically benefit various components of your business. Reach out to SGS Technologie- an experienced data analytical and DBMS software development company in Florida for further analysis. We are headquartered in Jacksonville and can give a more detailed description over direct meetings, <A href=\"https://www.sgstechnologies.net/contact\">phone calls</A>, and/or emails.",
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Data Management vs Data Warehousing

169

Feature	DATABASE MANAGEMENT	DATA WAREHOUSING
Processing Types	On-Line Analytical Processing (OLAP) is used to swiftly analyze massive volumes of data. This process gives the advantage of analyzing data from different perspectives.	Online Transactional Processing (OLTP) is used to delete, insert, replace, and update large numbers of short online transactions quickly. For example, number of units sold per day or even per hour can be derived.
Optimization	A database is optimized to update (add, modify, or delete) data with maximum speed and efficiency.	Data warehouses can be optimized to speedily execute a few complex queries on large multi-dimensional datasets.
Data Structure	Data in databases are normalized to reduce and eliminate data redundancy, which means databases eliminate storage of same data piece more than once.	Often data is denormalized and contains repeated data for easier access and to perform complex queries.
Data Analysis	A skilled developer or analyst is required to create and execute complex queries on a Data Base Management System (DBSM), which could require massive time and computing resources.	Data warehouses are designed to perform complex analytical queries on large multi-dimensional datasets. There is no need for knowledge of sophisticated DBMS software.
Timeline	Databases manage daily transactions for one aspect or department of a company. Hence, they typically will contain current, rather than historical data about one business process.	Data warehouses are used for analytical purposes and business reporting. They can store historical data by integrating copies of transaction data from disparate sources.
Concurrent Users	Databases support multiple concurrent users because they are updated in real-time to reflect a business transactions. However, only one user can modify a piece of data at a time.	Data warehouses support a limited number of concurrent users. A data warehouse is separated from front-end applications.
ACID Compliance	Database transactions are normally executed in an ACID (Atomic, Consistent, Isolated, and Durable) compliant manner. That is, database management systems can function even in the event of errors or power failures.	Data warehouses focus on reading instead of modifying, historical data that is derived from various sources. Hence, ACID compliance is not strictly enforced to a big extent.

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