archiving of financial transactions carried out within a point of sale or an online store;
Posted: Wed Jan 08, 2025 3:57 am
addition, the organization of the stored data is perfectly structured and accessible to all user profiles. In addition, one of the advantages of the Data Warehouse lies in its flexibility. Indeed, the information stored there can be updated continuously. But also, the data can undergo as many transformations as necessary depending on their use. Examples of digital information that can be stored in a Data Warehouse include:
all information concerning customers such as their identity, means of contact, or their purchasing tendency;
accounting data such bolivia phone data as archiving of purchase orders, invoices, logistics inventories;
maintenance histories of industrial or IT equipment;
information relating to human resources management such as employee identification records, recruitment forecasts, continuing and professional training plans;
storing company financial data with balance sheet, cash flow, KPI data;
data on the company's environment such as target customer demographics, age, geographic location, preferences and purchasing habits.
In any case, the Bachelor Data Science training allows you to precisely define the type of data storage system best suited to the company you work for. Indeed, depending on the size of the company, and the information used, its use, it is appropriate to define the solution capable of flexibility and adaptation to user expectations.
Data Lake: a system for storing large data
The Data Lake has the advantage of being able to quickly store very large volumes of digital information, but above all of being able to retrieve them securely. Indeed, it is necessary to provide encrypted identifiers in order to be able to exploit the information stored on this storage technique .
Unlike the Data Warehouse, in which information is stored in a structured manner, the data contained in the Data Lake is raw. Their exploitation then requires more patience, and above all a well-defined technique. We can find in this storage system information such as:
archiving all interactions with customers on social networks. This data is subsequently used to explore consumer behavior and draw productive analysis from it regarding the different marketing strategies adopted;
the storage of various banking transactions carried out online on an e-commerce site, for example. This digital information stored in the Data Lake is subsequently used to detect fraud techniques;
archiving of scientific studies retrieved in raw form as part of competitive intelligence. This information is then used for research purposes on targeted subjects.
Given the characteristics of the digital data that can be stored on the Data Lake, this system requires a greater capacity than the Data Warehouse. Furthermore, it can also be noted that the difference between the two storage systems lies in the fact that the Data Lake can contain raw information to be processed and filtered, while in the Data Warehouse, the data is already well structured for a defined purpose.
all information concerning customers such as their identity, means of contact, or their purchasing tendency;
accounting data such bolivia phone data as archiving of purchase orders, invoices, logistics inventories;
maintenance histories of industrial or IT equipment;
information relating to human resources management such as employee identification records, recruitment forecasts, continuing and professional training plans;
storing company financial data with balance sheet, cash flow, KPI data;
data on the company's environment such as target customer demographics, age, geographic location, preferences and purchasing habits.
In any case, the Bachelor Data Science training allows you to precisely define the type of data storage system best suited to the company you work for. Indeed, depending on the size of the company, and the information used, its use, it is appropriate to define the solution capable of flexibility and adaptation to user expectations.
Data Lake: a system for storing large data
The Data Lake has the advantage of being able to quickly store very large volumes of digital information, but above all of being able to retrieve them securely. Indeed, it is necessary to provide encrypted identifiers in order to be able to exploit the information stored on this storage technique .
Unlike the Data Warehouse, in which information is stored in a structured manner, the data contained in the Data Lake is raw. Their exploitation then requires more patience, and above all a well-defined technique. We can find in this storage system information such as:
archiving all interactions with customers on social networks. This data is subsequently used to explore consumer behavior and draw productive analysis from it regarding the different marketing strategies adopted;
the storage of various banking transactions carried out online on an e-commerce site, for example. This digital information stored in the Data Lake is subsequently used to detect fraud techniques;
archiving of scientific studies retrieved in raw form as part of competitive intelligence. This information is then used for research purposes on targeted subjects.
Given the characteristics of the digital data that can be stored on the Data Lake, this system requires a greater capacity than the Data Warehouse. Furthermore, it can also be noted that the difference between the two storage systems lies in the fact that the Data Lake can contain raw information to be processed and filtered, while in the Data Warehouse, the data is already well structured for a defined purpose.