The database is a platform necessary for the proper functioning of most digital applications. Its mission is to quickly collect, process, and analyze data from websites, internal reporting, and marketing tools. However, these platforms are not always efficient.
This is often due to a poorly identified need and more generally to sloppy management of the project upstream. For proper use of the database, it is necessary to respect some key points during its implementation.
1. Identify the Need
This step may seem elementary but is often overlooked. We often only realize this once the database is in production. The objective here is to clearly identify its need. Specifications will be needed to present your project to the various service providers including auditors, software publishers, hosts, etc. This involves defining the use, the desired levels of security and availability, identifying the type of application that will connect to the database, and also planning to assess the volume and plan the growth of the platform like capacity planning.
Focus on data, not apps. Applications come and go. Data, on the other hand, is the asset of your company. Although developers are often in the mindset to deliver databases quickly, it is good practice to think ahead about the future functionality that will be required of the database. If some features are missing because you don’t need them right now, someone will come to you about them one day. It could even be you, or your successor.
2. Consider Administrators by Design
The data is used in such different ways that it is complicated for a database designer to go around the question of use. The latter should therefore not wait for the final phases of construction, or even delivery, to speak with the database administrators.
Because often this approach produces a tool that does not really meet the needs of administrators. For example, naming conventions that identify database objects must be shared between designers and administrators as soon as possible. At the same time, administrators do not necessarily have time to have coffee with designers to discuss their moods. Developers must therefore learn to think like a DBA to deliver good databases.
3. Define the Database Model
Two major database models are identified— the transactional model and the multidimensional model. The first is generally used for web applications and the second is more for business intelligence databases. For CRM-type platforms, the model will depend in particular on the need and the functionalities sought.
The transactional model will generally make it possible to respond to elementary queries by crossing several tables to present, for example, all the products that correspond to the criteria indicated by the customer. The decision-making or multidimensional model, on the other hand, executes more complex queries based on history and external data to eventually move toward Big Data. Its star or snowflake diagrams make it possible to cross several dimensions including date, place, articles, etc. to generate an activity monitoring report or to define the future strategy to be adopted.
Yes, software engineering is important, but many developers shy away from using data models. Data is the memory of a company. It can decide to redevelop or buy an application to be more efficient, but nothing will be more efficient for the consistency of its activity than using models.
4. Choose The Database Management System
Depending on the database model, one often has to choose between an open source editor and an editor with support. The choice of one of these solutions will depend in particular on the budget, the level of support desired, the internal skills in technology, and the expertise of the service provider. The chosen system must meet all the needs and constraints including security and availability.
Some DBMSs have, for example, security mechanisms already integrated and offer automatic failovers that meet a Disaster Recovery Plan. This will save time on the implementation of such actions and avoid possible maintenance costs on solutions developed in-house.
5. Plan your Infrastructure
Then focus on the infrastructure that will support this platform. Should you host it internally or outsource this part? In the case of internal hosting, you must ensure that you have the skills to outsource it, especially for high-volume databases that require regular maintenance. If you choose to outsource, it is necessary to choose your service provider carefully. Here, Everconnect is such a reliable managed database service provider.
Anyway, to do this, you must define the hosting mode in the particular cloud, physical, etc. and the level of support desired. So-called low-cost hosting or a basic cloud solution without support is often recommended for small volumes where the database does not require a high level of security and performance. Conversely, a specialized host will offer specific support, the customer can then be advised in the choice of his hosting solution namely the number of machines, hardware, virtualization, etc. and benefit from appropriate outsourcing.
6. Optimize your Database
Before going into production, it is essential to test your database to ensure that the system remains responsive and supports the load. The architecture will be checked during normal activity and periods of heavy load will be simulated to know precisely the limits of the solution. The results will make it possible to validate and adjust several points— the sizing of the infrastructure, the need for software tuning, the correct indexing of the database, etc.
7. Follow and Maintain the Platform
Once the database is in production, it is important to monitor it daily. Regular contact with the customer is essential to get the user experience. Supervision, for its part, provides objective data on the performance of the platform. This then makes it possible to initiate maintenance actions like software updates, platform, etc. and to ensure the security and availability of the application.
Sometime after the start of production, you need to check that the growth forecasts were correct and you anticipate the evolution according to the real history of the platform but also the context of the company. The need as it had been defined evolves. Security can become an essential criterion. The decision to develop the platform or even change the management system may then be necessary.
To Sum Up…
If the structure of a database is optimal in a specific case, it cannot operate everywhere with the same efficiency, especially in terms of the data access path. So the trick is right from the start to build structures that allow access to data in different ways. Again, during the modeling stage of the database structure, the management of the data access layer should not be forgotten.