BI – Business Intelligence could be defined in many ways, each reflecting a utility or a prominent feature of BI. The tools of BI from data mining, analysis, and efficiency measurement all aim at one ultimate goal: supporting decision making.
A common decision-making process is shown in the following figure:
BI and the non-technical transfer
The history of formation and development of BI tools is closely linked to computer science and the need to explore human information.
Phase BI 1.0 lasts from the late 1990s to the early 2000s.
BI 1.0 almost focuses on data processing. In this stage, the ability to map and analyze data on BI tools has not been focused and exploited.
BI 1.0 is considered a “luxury” concept due to two main causes: Implementation cost and exploitation efficiency.
Implementation costs include software copyright and deployment services. With deployment services, requiring employees who deploy must have a wide knowledge of both IT and data analysis, so the deployment resources of BI are not plenty. Therefore, deployment costs increase.
Resources for using BI for analysis are finite. Because this BI system can only be used by individuals with IT profession and knowledge of data processing and analysis. While the cycle of need for analysis is infinite. Starting from data collection, aggregating it into a report, based on reports for decision making and action. After acting out the results, there will be a need for new analysis and repeated cycles.
The more organizations have a requirement for reporting and analysis, the more congested the information flow will be as a funnel, with a funnel knot is the IT department. In order to have a report for decision-making needs, the requester will be required to wait an average of 2 to 3 weeks. And this makes the BI system ineffective.
The BI 2.0 phase began in the late 2000s, when the development of the Internet and Web 2.0 opened up a tremendous amount of information and led to strong demand for data analysis for all parts, not focus only in C-level as before.
All IT and non-IT objects can operate this phase BI system, allowing users to self-explore data to find answers directly without queues as stage 1.0.
TABLEAU BI – DATA ROCKSTAR
Along with the trend of Modern BI 2.5, Tableau BI is considered one of the pioneering solutions with outstanding features. Tableau BI features a suite of solutions suitable for all types of organizational models and user needs. With 6 functional groups covering requirements. Tableau BI also supports many installation models and extension methods to help organizations make easy choices according to each time of development.
From version 2018, users no longer need to worry about data storage scattered in the business but simply with drag and drop, data sources merged and standardized will be ready for analysis. With Tableau Prep, Tableau’s ambition is to create an ETL tool for users who are not necessarily IT.
With 10 years of development, from a Stanford University project, Tableau has released 21 versions of Tableau Desktop products, constantly updating features.
Tableau Desktop is a prominent name in BI platforms when it is possible to reconcile 3 factors: Database, Human-Computer Interaction, and Computer Graphic.
It’s hard to believe that with just 2-3 clicks or dragging an information field from the list of dimensions, users have an impressive report right away. For Tableau, instead of focusing on thinking about how to display an optimized data content, users only need to really focus on their data needs. All other issues including optimal display selection, optimal color schemes, analytical suggestions will be completely implemented for you by Tableau Desktop. Tableau is the solution to the infinite loop demand problem of BI 1.0.
The characteristics of information are time. Information is only valid for a short period of time. Therefore, accessing the reporting system anytime, anywhere under any type of device is a mandatory requirement for BI 2.5. This demand is handled flexibly with Tableau Server products. Users after creating reports on Tableau Desktop can publish to Server and store there. Any authorized user can access it to view the report at all times or set up alerts to send to mobile devices according to specific management needs.
According to the famous magazine The Economist, the world’s most precious resource is no longer oil, but data. With BI, organizations have a tool that allows them to explore the most valuable data sources and create a premise to be able to move faster in a competitive environment.
“The world’s most precious resource is no longer oil, but data” – The Economist
TABLEAU BI Deployment
Since 2017, Tableau and FPT IS have organized many activities such as seminars and workshops for Vietnamese enterprises to have opportunities to approach Tableau BI and experience the products.
With the model aimed at all types of business organizations, Tableau has flexible and neat deployment methodology with a focus on helping users operate and exploit the system (Self-Service). Implementation costs for Tableau BI are also reasonable. Moreover, the organization can adjust the number of users depending on the number of users and the number of months to use. This reduces the burden of licensing costs.
Based on the deployment experience of general BI and Tableau BI, in particular, the necessary steps businesses can take to successfully deploy Tableau include:
- Training users on solutions.
- Determining the management needs of businesses.
- Preparing data sources according to KPI needs.
- Directly using Tableau to graph the data, analyze, make decisions, and repeat cycles.
With BI, the most important key to success is building a data culture. Data culture is associated with critical thinking. Before any information content, each individual in the organization must have critical thoughts about that information. This is the source for the need to search for information and analyze information to make decisions.
Of course, cultural construction is a long process with many steps in the roadmap. However, organizations need to do it early and start from the smallest. Right now, equip users in the organization with a tool to analyze data and show them how to approach the problem. Sowing down to many small patches of the forest will be a premise for a big forest.
Tran Thai Giang – FIS ERP HNRelated posts: