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Data is a vital asset in a modern business, and companies need effective data management and utilization to stay competitive. However, many organizations and businesses face various data-related challenges, such as lack of data visibility and difficulty in using data, making it difficult to put data to practical use. Even if you try to use and utilize data, it may be difficult to put it into practice due to lack of data visibility, difficulty in using data, etc.
A "data catalog" is used as one means to address these issues. A data catalog is a system that manages metadata that describes the attributes and characteristics of data.
This article explains the benefits and construction steps for those who want to build a data catalog to promote data utilization. In addition, for those who are wondering whether to actually produce it in-house or use a tool, we will explain the advantages and disadvantages of each and the points to consider when selecting a tool, using relevant case studies.
First, let's understand why data catalogs are useful for data utilization.
Data is often spread across multiple locations within an organization, making visibility difficult. A data catalog organizes this chaotic state and centrally records the location, characteristics, and usage of data. As a result, system users can smoothly find the data they need and greatly reduce the time it takes to search for data.
Especially in large and complex data environments, a data catalog can help data engineers and data scientists spend less effort acquiring data and more time focusing on strategic analysis. This easy access to data saves valuable time for data users and improves efficiency across the organization.
Data quality and reliability are of the utmost importance when utilizing data. By implementing a data catalog, you can manage metadata to collect information such as data characteristics, statistics, sources, owners, and update history to improve the understanding and reliability of your data.
Providing this aggregated information allows system users to verify that the data is accurate and avoid making decisions based on incorrect data. Data catalogs also support regulatory compliance and improve security by clearly documenting where data comes from and how it is used as part of data governance. Improving data quality by introducing a data catalog will make it easier to make strategic decisions using accurate and reliable data.
Let’s understand and acknowledge step by step what you need to do to build and utilize a data catalog.
The foundation of a data catalog is a thorough understanding of the needs of your analytics users. We identify the uses and needs of data within an organization, and identify issues such as what should be made easier to search by introducing a data catalog. This makes the purpose of the data catalog clear and enables effective design.
Building of the required metadata schemas as requested by your analytics users. This means defining and linking each element, including data characteristics, sources, relationships, historical information, and access rights. This enables accurate data understanding and rapid data retrieval.
Based on the metadata schema you build, we collect metadata from your data sources and integrate it into the core database of your data catalog. This process enables unified management of data and improves data discoverability and accessibility.
Security is of absolute importance when building a data catalog. Ensuring data protection through strict access permissions and security policies for data in your data catalog ensures data confidentiality and protects your organization from unauthorized access.
To keep up with your ever-changing data environment, update your data catalog regularly as new data sources are added or metadata changes. This keeps your data catalog accurate and applicable, supporting data-driven success.
Data catalogs are very convenient if you can make use of them, but there are different advantages and disadvantages whether you create a data catalog in-house or use a tool.
Producing a data catalog in-house has the following advantages:
The in-house created data catalog can flexibly respond to a variety of data needs. By creating a data catalog in-house, one company has become able to accumulate data from all services and provide an integrated data analysis environment. This has led to the democratization of data, making data accessible to a wider range of users.
An in-house data catalog allows us to strictly control data access privileges, ensuring data security and privacy. This allows you to minimize the risk of leaking sensitive information and control access to your data.
As mentioned above, creating a data catalog in-house means that you can create a highly customizable system that better fits your requirements, and can cover the many requests of members within your organization.
On the other hand, in-house production of data catalogs also has the following disadvantages.
In-house data catalogs are expensive to design, implement, and maintain. It requires investing a lot of resources and time, which requires proper allocation of budget and resources.
There is a risk of technical challenges in dealing with large data environments. Optimizing performance and ensuring data security can be difficult and requires proper design and scaling.
To utilize an in-house data catalog, you need people with specialized data knowledge. This means that it is necessary to secure data engineers and data governance personnel.
Data catalogs must keep up with changes in the data environment and maintain data accuracy and freshness, so regular updates and customization are essential. This requires additional resources and time.
In this way, when creating a data catalog in-house, it is necessary to secure resources such as effort, time, money, and expertise.
When you use a data catalog tool, you can enjoy the following benefits:
Tools help you organize your data's metadata (information about your data) and enable quick searches of your data. This allows you to reliably locate your data and facilitates intuitive visualization of your data.
By adopting a data catalog tool, operations can be automated and the total number of data assets can be understood and managed. This makes it easy to discover datasets, tag metadata, and organize data to improve both business and technical context.
Although it is a very useful data catalog tool, please be aware that it has the following disadvantages.
Implementing and maintaining data catalog tools is costly. This includes licensing costs, hardware requirements, training costs, ongoing maintenance, and more, which organizations must budget appropriately.
Proper configuration and customization of data catalog tools may require technical knowledge. As data becomes larger, performance optimization and security measures also need to betaken care of, and resources need to be reserved for these.
The advantages and disadvantages of introducing data catalog tools like these are discussed in the following two articles.
Related article
Based on the above advantages and disadvantages, we will explain the points to consider when selecting a data catalog tool that can make your work more efficient.
Among the success factors in data cataloging tools, the first thing to note is the flexibility and extensibility of the metadata. This includes being able to customize metadata to suit the characteristics of your data and your organization's business needs. For example, you can easily associate business terms with physical data items or add new custom metadata fields for flexibility and extensibility.
Controlling access to data is also a very important element of data catalog tools. The ability to finely manage access rights to data and set access rights according to users and roles is essential.
Also, check to see if they offer strong encryption when storing and transmitting your data. Ensuring that data is transferred and stored securely is an essential security measure.
The success of a data catalog tool also depends heavily on the user experience and support structure.
When it comes to usability, the key is whether the tool is intuitive and easy to understand for users. Specific evaluation points include an easy-to-use user interface, a help function for how to use, and ease of use that even non-engineers can use. Thus, it is extremely important that users can operate tools smoothly and maximize the value of their data.
Ease of operation is also a consideration. If the number of operating members is small and the setting items are simple, the tool can be operated efficiently and smoothly. Other than that, we also evaluate the provision of comprehensive manuals and training materials, and the support system within the budget.
The following two factors are essential to effectively utilize such a data catalog.
The foundation of a data catalog is accurate and detailed metadata. Metadata reveals the essence of data, allowing it to be understood, explored, utilized, and effectively managed. The quality and accuracy of metadata enhances the reliability of data catalogs and supports strategic decision-making.
Metadata includes the following elements:
Accurately recording and properly maintaining the above elements is essential to maximizing the value of your data catalog.
A successful data catalog requires a thorough understanding of the needs of analytical users and a data catalog designed to meet those needs. Here are some steps you can take to understand your users' needs:
First, identify your increasingly diverse user base to understand your data catalog requirements. Get a clear picture of which user groups need access to what data.
Once your users are identified, fully understand their needs and translate them into specific requirements for your data catalog. Design and deliver a data catalog that matches what your users are trying to accomplish.
If data catalogs can be used, it will be possible to promote the democratization of data and improve the quality of data used within an organization, helping to improve operational efficiency and data-driven management.
If a data catalog can be produced in-house, it will be able to better meet the needs of each individual, but it usually requires significant resources such as cost, time, and personnel.
The data catalog function of trocco® has the following features and can be expected to have great effects while keeping costs down.
Improved problem solving and usability
We solve usage problems from the basics to advanced stages of data analysis. Efficient data utilization is possible because metadata can be automatically acquired and utilized, eliminating the situation where the location and contents of data are unclear.
Self-growing data catalog
Metadata automatically increases and accumulates as data transfer settings and data marts expand. The burden of metadata management can be greatly reduced by eliminating time-consuming metadata entry work and allowing the data catalog to grow on its own.
Table details screen to support data understanding
trocco®'s table details screen allows you to easily view detailed metadata for the table and each column.
In addition, extensive preview functionality is provided, including support for displaying summary statistics for each column and filtering and sorting on the table preview. This allows for smoother data handling and faster data understanding.
A query editor that will satisfy even engineers
You can create queries with one click from any screen, and the auto-completion function and metadata display support query creation. It also has a variety of functions such as saving queries, previewing execution results, and exporting results to CSV.
For those who would like to know more specific solutions to solve such problems, please contact our Sales Support Global Team and we will be happy to help you !
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