What Is Data Lake? The Pool Of Corporate Knowledge
A correct data analysis and management activity begin with data collection. This is why the Data Lake exists, a database where all company data is concentrated without the need to be structured. The Data Lake takes its name from the concept of a lake where a pool of data is stored, including images, text files, tables, free text, etc. It’s crucial because it allows companies planning any data activity to start storing it. Suppose the main objections for many data management projects concern the duration and complexity of the interventions. In that case, the Data Lake is used to get ahead by collecting everything that can be useful.
Furthermore, the very essence of the Data Lake allows it to be connected downstream with any tool for structuring data. It can therefore become the storage base for your corporate Customer Data Platform. In summary: the Data Lake is a type of repository to store data sets of various sizes and types in their raw format. Precisely for this reason, it can support the analysis activities related to the CDP. Collecting company data makes them available to the Customer Data Platform, which no longer needs to be connected to multiple systems but can draw from a single significant source. Finally, tomorrow’s CDPs will likely be different than today’s, so it’s essential to keep the data in its raw form, so it can always be helpful and readable in the future.
What Is The Data Warehouse? The Company Library
To understand the Data Warehouse, we have to go back to 2005. The concept of Data Lake was not widespread, and there was talk of the importance of collecting data, yes, but already structured. The Data Warehouse is, in fact, a container of tables optimized for reading and, therefore, ready for analysts. It’s the place to look for corporate knowledge within tidy, clean and certified data. You can imagine it as an extensive library.
The content of the Data Warehouse can become the evolution of what is collected in the Data Lake. With the advent of the Cloud, the two technologies are now so interconnected that we can speak of DataLakeHouse. At the business level, neologism indicates the set of tools that take the company from not having any data collected to a series of tables that can be read and used for Business Intelligence activities.
CDP, The Red Thread Linking Business And IT
Both the Data Lake and the Data Warehouse share what may be a limitation: the lack of business accessibility. They are often tools managed entirely by IT teams which, in turn, are overloaded by the number of requests. This is a decidedly relevant topic for organizations that decide to do data-driven business activities. In this context, a Customer Data Platform can become the critical tool to meet both needs. Another relevant difference between these solutions concerns the data collected: if Data Lake and Data Warehouse contain data of any kind, from production to finance, the Customer Data Platform focuses explicitly on data relating to Customers, prospects or customers who are.
It, like this, deals with the core of an organization’s real business. We should return to its definition briefly: when an organization considers CDP, it, as a rule, alludes to two arrangements of numerous arrangements. Because of the CDP that produces knowledge, we are discussing an information base that can depend on an Information Lake and begin with organized and unstructured information to create talking reports. In this, the Customer Data Platform is evaluated on its ability to:
- combine individual customer information into a single view, or single customer view (SCV)
- do lead scoring
- support the business with audience segmentation activities
- return advanced results through dashboards and analytics.
In the second case, the Customer Data Platform becomes the tool that enables a data-driven system engagement with people in general. It is, like this, a framework ready to “tune in” to the information gathered from different sources, permitting the business to do showcasing and business activities continuously. Anyway, the CDP allows you to draw an obvious conclusion regarding every piece of information, making it open and usable at the specific time required.
What Are The Differences Between CDP, Data Lake And Data Warehouse?
The Type Of Data
The Data Lake is the device that, as we have seen, gathers all organizational information in its rawest structure. Simultaneously, the Information Distribution center is an organized arrangement of tables prepared to help with all sorts of examinations throughout the organization. The Client Information Stage oversees unstructured, semi-endlessly organized client information, guaranteeing the protection of shoppers who connect with your organization and controlling the information stream between various sources.
How Data Is Managed
A Data Lake stores data in its original format and therefore does not transform or unify it in any way. Instead, a data warehouse reformats them into tables. Finally, the CDP can take multiple data formats and bring them together, returning a single view of the customer, which is essential for any business.
Who Uses Them
The Data Lake is the ideal tool for data scientists who want to test algorithms based on artificial intelligence. The Data Warehouse is mainly used by analysts who carry out the company’s reporting and business intelligence activities.
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