Slow. Inflexible. Time-consuming. A few years ago, traditional BI was the only option available. But today, does this sound like the best way to get users the business insights they need to do their jobs? Not really. Businesses can either go one way with centralized BI run by their IT department or they can opt for a modern BI solution, bringing us back to the age-old debate – traditional vs self-service BI.
There are pros and cons to be considered before making a choice.
Table of Contents
Should you choose traditional BI?
There are reasons for this controlled BI environment to exist.
When you control the data and the BI application, you can control the quality of the results.
IT departments entrusted with the task of maintaining data quality ensure that data is properly prepared, stored and secured.
They build systems that offer standardized, scalable self-service reporting and they give users answers to their business questions.
Sure, those answers may take a little time to materialize, especially if the IT department is busy with other projects. Or if the rate of growth of data (and big data) starts to outstrip the IT department’s bandwidth.
Is self-service BI an alternative?
Self-service BI has made giant strides to get to a point where users can access data from multiple sources, get insights and make faster business decisions.
The tools are typically intuitive and interactive and let users explore data beyond what the IT department has curated.
Benefits of self-service BI
The expanded data access and analytics capabilities that self-service BI provides can benefit businesses in a variety of ways.
1. Better use of BI and IT resources
Because business users can do their own ad hoc analysis, self-service BI frees an organization’s BI and IT teams from creating the majority of queries, visualizations, dashboards and reports. That allows them to focus on higher-value priorities and tasks that require more technical skills, such as curating data sets for business users and creating complex queries.
2. Faster data analysis and decision-making
Self-service capabilities help reduce bottlenecks in BI programs by shifting analytics work to business users instead of a small number of BI professionals. That in turn accelerates business processes, because users can more quickly analyze data and then make decisions and take actions.
3. A data-driven organization
As more business executives, managers and workers use BI tools, self-service systems can help create a fully data-driven culture in both the C-suite and business operations.
4. Competitive advantages
The expanded use of data and accelerated decision-making can make an organization more agile, which may help it create or maintain a competitive edge in the marketplace — particularly if its use of self-service tools is more substantial and successful than similar efforts by business rivals.
Questions to consider when comparing traditional BI with self-service BI
- What are the upfront costs, implementation costs and even the annual maintenance and support costs?
- Also, have to estimate how much time/money/resources are needed to train the end-users to use the solution?
- What technical resources & skills are required to access, prepare and make data actionable for the end business user?
- Does the solution allow a business user to connect to existing data sources? How easy is it to add a new data source? If they plan to do something like changing the Data source or switch the Server, will that be achieved without help from IT?
- Can Business Users access real-time data and view reports from their mobile devices?
- Who watches the data? Is there a security layer to control business user’s access to view data as well as reports based on their role and department?
Traditional vs self-service BI
Traditional BI implementation is resource-intensive whereas self-service BI is a ready-to-use tool.
As a business owner or stakeholder exploring BI tools, the question for you remains—which of the two is right for your business?
For a broader evaluation of both options, let’s dive right into a detailed comparison between the two.
| Traditional BI | Self-Service BI | |
| IT Setup | Majorly IT-driven with near-constant involvement of IT and data specialists. Legacy deployment with multiple components, each requiring specialized personnel to implement and maintain. | Once implemented, it frees up the IT staff to focus on other infrastructural requirements. Also, it reduces the number of specialized IT personnel needed for maintenance. |
| Agility | Access is restricted to IT personnel and data specialists. Market opportunities might remain trapped inside week- or month-long cycles of queries and reports. | Users can do data analyses and generate reports and insights in real-time. They can also test hunches about trends and correlations by modeling data on the fly. |
| Data | Need to structure the data before it can be utilized. | Harness data in various formats from multiple sources. |
| Reporting | Focused on answering questions about what happened in the past or is happening right now. Limited capabilities of on-demand reporting. | In addition to historical reporting, it provides predictive and prescriptive reporting with a forward-think approach. Diverse on-demand reporting capabilities. |
| Data governance | Close involvement of IT staff and data specialists ensures cleaning, proper storage, and security of data, and addresses concerns about data governance. | Need data governance policy to define processes for cleaning and storing data, considerations for data modeling, and privileges for data access. |
Can you use both?
Perhaps, an organization may need both traditional vs self-service BI.
Functional reporting on daily business operations is still a common requirement in organizations today.
Compliance reporting and dashboarding, for example, are still the need of the hour.
Traditional BI still has a role to play in answering questions about what happened in the past or about what is happening about operations now.
For questions about the future, especially impulsively “what if” style questions, users want more individual power and faster reaction times. In this case, self-service can be preferable.
Navigating both traditional and self-service BI
How you navigate between traditional vs self-service BI will depend on three factors. Identification of suitable self-service BI use cases is one factor.
Business user levels of BI understanding is second.
Finally, data governance and the commonality (or not) of BI systems.
We look at each in turn, below.
Self-service use cases
- A retail company may want answers the same day about which products to put on special offer or how to adjust its daily online advertising.
- A restaurant chain searching for new dishes may want to look for “fail fast analytics” to quickly explore test market reactions and eliminate experiments that it does not find favor.
- A supply chain company may want to consolidate spreadsheet data sent in by subcontractors to immediately spot any signs of rising costs or delays that could jeopardize the business.
Levels of BI understanding
If a deep understanding of BI or data science is needed for a BI application, then that application is unlikely to be self-service.
A self-service tool is sufficiently intuitive and allows users to focus on business results instead of underlying technology. End-users can work independently of developers, data specialists and the IT department.
One example is smart data visualization allowing ad hoc questions to be easily asked about any part of the data and to any depth.
Self-service BI and the question of data governance
Self-service BI cannot be at the expense of confidence in the results.
Self-service tools that can use data sources directly can avoid such problems.
There may still be a discussion about the way the results are to be interpreted, but there should never be disagreement about the sources or the consistency of the data used to get the results.
Is the future of BI self-service?
There is a possibility that traditional and self-service BI will continue to coexist. However, constantly rising data volumes and ever-growing business needs will mean that end-users will do an increasingly large part of BI for themselves.
Self-service BI applications will let users focus on their business questions without needing to build elaborate solutions, get the insights, and answers they need immediately, without having to wait for specialist IT staff to help them out.
Self-service BI trends to watch
Augmented analytics technologies are increasingly becoming core components of self-service BI platforms.
They include natural language querying capabilities that eliminate the need to write queries in SQL or other programming languages, as well as AI and machine learning algorithms that can identify relevant data, explain the meaning of data elements, automate the data preparation process and suggest appropriate types of data visualizations.
Gartner predicts that augmented analytics features will be “ubiquitous” in BI tools by 2022.
Other notable trends include the rollout of low-code and no-code development tools by vendors to simplify the process of creating BI applications, plus the addition of support for multi-cloud environments to BI platforms.
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