Value of the Graph Database #1.
Effective and Efficient “Data Modeling”
Recently, new technologies like personal devices, IoT, social network, blockchain, AI, etc. are reorganizing the data into a more complex, highly connected form.
And being aware of how large and various data we have become almost impossible! So, now the question left for us here is “Are you efficiently utilizing and managing it?”
Whether you already heard of it or not, Graph Database is being recognized as the soaring eagle in this era flooded with highly connected large size of data.
We have a long way to go to show and present the true power of Graph Database for businesses.
But when we turn our gaze on the world market, many businesses are already utilizing it for various areas such as recommendation system, social network analysis, AI, financial fraud detection, big data processing, and else in the field.
What’s so special with Graph Database when compared to the RDB(Relational Database) we’ve used till now?
There are numerous benefits and values from Graph Database we’d like to introduce to you, and in this posting we first want to talk about the Effective and Efficient Data Modeling, powered by Graph Database.
“Graph Database” Enabling Intuitive Data Modeling for Cooperation!
Graph Database provides intuitive “Data Model” which is very close to the real business model in our daily lives, consisting of data objects and relationships that connect those data objects to each other.
The data model from Graph Database reflects the reality in a surprisingly similar manner and offers easy and quick modification to the data model, so your business can enjoy high intuitiveness and great flexibility from it.
Traditional RDB models and manages data by creating tables with many rows and columns.
In other words, if we want to model the data, streaming from the real world business, we have to analyze and reorganize them to fit in the existing RDB, resulting lower intuitiveness of data model.
This reorganizing of data model gave birth to basically two kinds of problems:
One of them is that we suffers from unnecessary workloads during the developing process, and project participants experience difficulties in understanding the structure of database in their system.
The second problem comes from the model’s complexity, which gets worse and worse over time, to reduce the flexibility of database. It means that decision makers like CEO and managers in a company whose expertise is not in database are going to have hard time to use and exploit data!
With the rise of the need for efficiently utilizing data ─ collected and handled for many purposes inside a company ─ it became much more important for employees to understand the data structure of what they are doing in their company.
Moreover, as a variety of different kinds of data are frequently used in the field, collecting, processing and analyzing the data is no longer a work only for data engineers, and it is becoming everyone’s task including ‘C-levels’ and all employees in other divisions.
When you organize your data with Graph Database, you will find your data model intuitively reflecting the real world business and fields that are available for utilizing data expanded. By implementing Graph Database, now all of your employees can access, analyze, and use the data, including non-experts in data engineering!
Also, the intuitive modeling that Graph Database offers works as a great advantage in the time for developing system and operating with data.
Have heard of the latest Agile Software Development ?
For those who haven’t, let us briefly introduce what Agile Software Development is. Agile Software Development is a new software development approach to overcome problems of previous ones. It first starts with setting the development time frame and once developers set new objectives, repeat tests and re-development of the software until final goal is met.
This kind of approach may require continuous modifications to database design with the changing system environment during the development time frame, and a data model that everyone who participates in the project can clearly understand.
When we use RDB we have to work on each table based on the schema(design) and if the system changes a lot of unnecessary, multi-stage tasks derive. The result? Project members cannot easily understand the data model, the quality suffers, and put members behind the schedule.
With Graph Database, you don’t need a schema at all and benefit from faster development, test, and system modifications than before.
[RDB vs. GDB: Which one intuitively & effectively models the real world?]
(It is pretty evident that graph data model reflects the real world model when you compare graph data model with the real one.)
Recent rapid changes in the market trend drive businesses toward effectively discovering and utilizing the hidden value from data, rather than just securing large amount of data.
In this perspective, RDB environment could be designed/organized/managed by only a small number of experts, and it is destined to be unable to instantly react to changes and adopt improvement by its nature. On the other hand, it is possible for field employees to feed unnecessary data to the system.
For example, if taxation staffs who actually know well about tax law revision could explain the business flow by himself and model it through Graph Database, this would make your business much more efficient by avoiding problems you don’t want to face with.
The intuitive modeling capability of Graph Database can bridge the gap between the real world model and the data model in your system.
Consequently, you are able to easily understand, utilize, and improve the data flow across your organization.
The next horizon for big data management?
It is Graph Database, a platform guaranteeing the variety, flexibility, and intuitiveness of the stored data.