The Journey from Traditional BI to Self-Service Analytics
The size of data on the internet is exploding day by day. By 2020, the data we create and copy will reach zettabytes. Ample amount of data is created and managed by organizations. Data Management, Analytics, Governance, and Security are some key significant challenges that everyone from an individual to an organization faces.
Why Self-Service Analytics?
Traditional Business intelligence systems are less effective in managing such huge volumes of data. There are cases where the data integration phase runs into years. Also with unstructured data, it becomes very difficult to recognize patterns in tables and the more traditional BI display methods. Now here’s where self-service applications come into the picture. Self-Service is more about giving the business user the complete power of the data they require to make informed decisions instantly. The power of data is with the business users. They no longer have to reach the IT team with minor changes to the reports or dashboards. They have the data and the tool required to get the exact result that they want. The mail chain between IT and the Business users and also the time constraints are totally removed from the equation.
According to Gartner Inc., the balance of power in the BI world is shifting from IT to the Business. They have also predicted that by 2017, most business users and analysts will have access to self-service tools. This doesn’t mean that the IT team is out of the picture, they will still be an integral part in certain complex tasks and implementations. A framework or a layer has to be created by the IT team which the business users can leverage and use accordingly.
Let’s discuss the challenges faced in adopting self-service analytics:
Technical and Analytical challenges
When I was interviewing for a firm, the plan of the company was to migrate from the traditional BI applications to self-service business intelligence applications. The organization needed someone to convince the Business users and Analysts that the task can be achieved. To tackle such problems, proper training and encouragement to the business users would be handy in this case. The challenge was for the business users and financial analysts to adapt to the newly emerging self-service technologies.
It is quite possible that some users are not able to understand the data, in this case, the user would not be able to ask the right questions. So, understanding the business data would go a long way in helping users ask the right questions. Once the user knows what he wants exactly, he will have drag and drop options or he can write simple queries to build reports quickly with the help of self-service BI.
As the volume of data increases, the data sources will also increase with it. Data preparation and cleaning would be more time consuming than it was before. Sometimes the underlying data is too complicated for the business users to access in raw form. Increased analytical maturity and a better understanding of the technology platforms would help in resolving this issue in the future for the business users. The challenges associated with data can make a BI project go in vain, here's a post that enlightens about the consequences in detail.
Too much control to the user
A user who is not well aware of the queries and basic database skills can create problems for the organizations adopting self-service BI. Inefficient queries can lead to performance degradation and database problems. So, this is an area which can be resolved through proper governance. There must be a balance between user control and access while still giving the users the data and tools to create their own reports and dashboards.
Can Traditional BI and Self-Service Applications work together?
The main question for businesses now is “Should they go for enterprise solutions or self-service applications for BI”. The right option for any company, in this case, would be to go for the tool that fits their needs. Several factors such as organization’s budget, use cases, a level of technical expertise would play a significant role in answering the above question. The challenge for Business Intelligence developers is to bring in a new system that can successfully integrate enterprise and self-service tools in one or build a self-service application that takes governance and security under consideration. So, the real question at the end for businesses would be “How can they build a BI system from enterprise and self-service tools to satisfy their needs?”.
To conclude, the power of data would certainly help the executives and the business users in quick decision making. Having a single unified view of data across different departments would help each of the departments to identify the trend and build future strategies. Also, let's think of the time saved for the data analysts and data scientists to answer these business questions, they can use this time to build new products for the future. In the end, I would like to state that self-service analytics is here to stay and the future looks very bright.
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