As organizations shift their approach to analytics, IT leaders should seize the opportunity to redefine their role.
Adopting a collaborative approach to truly support self-service is the key to changing the perception of IT – from a producer to a strategic partner and enabler for the organization. Collaboration between the business and IT is critical to the success of the implementation. IT knows how to manage data and the business knows how to use the insights to drive business decisions. Early collaboration will not only lead to the deployment of a platform that meets the needs of the business but also drives adoption and impact of the platform overall. Indeed, in the 2015 Magic Quadrant for Business Intelligence and Analytics platforms, Gartner placed self-service data discovery tools designed for end users firmly in the forefront of the leaders’ quadrant.
Data Experts vs. Data Users
Owing to their complexity, traditional business intelligence (BI) tools have always been handled by data experts, meaning decision-making was limited to a privileged few. But not anymore. Today, In the world of BI, it’s all about the business user. Forget about those old tools that only data scientists or the IT department could use. In today’s fast-paced business environment, no one can afford to take weeks or months to prepare a report. It is all about being agile. Business users, at different levels, are able to access the real-time data they need & quickly generate results without the need for working on spreadsheets & any technical expertise. Often, no coding skills are required & even the reports can be sliced & diced as required without the use of Excel Pivots or any other methods of aggregation in SQL. The future is self-service, data discovery and quick insight—bringing power to the business users!
IT Governance vs. Empowering Users
As a self-service business intelligence solution, Self Service BI empowers the end user to seamlessly carry Self Service Data Analytics processes or Self-Service Reporting, without being heavily dependent on IT. When compared to Traditional BI, Self Service BI have a shorter development cycle that uses less IT resources and is quicker to deliver as well as easy to deploy on multiple platforms & devices. For example, reports can be accessed through smartphones & tablets. Because of the rich user interactive feature, user adoption is typically greater with Self Service BI than with Traditional BI as it is easier for any non-technical business user to understand & leverage. In Self Service BI Analytics, Data discovery is quick & easy, as it helps business to overcome the hurdles of Data Extraction & Data processing tools & pull data from different sources within their organisation (including the core data pipeline) to answer ad-hoc one-off questions. Once the Data-model is architected properly it helps information savvy users to get their answers fast without spending additional time on data-processing.
Self-Service Business Intelligence Governance provides ways for enforcing quick & affordable data governance. Business users are often unaware of the complexities of data preparation and the risks involved in getting it wrong. Without an authority guaranteeing strong data governance, they may miss mistakes in their own data, and draw the wrong conclusions—or different business users may draw upon poorly curated data sets, and reach different decisions. To prevent this, IT will most likely need to get involved.
Standardization vs. Customization
Each end user may be asking different questions, and looking for different answers. With flexible in-memory acceleration, users are able to create reports and answer questions for themselves, rather than having an IT department create reports for each question/user. Especially as data volumes grow, this becomes increasingly critical. With this in mind, self-service reports can provide a huge boost to productivity, as they can be personalised based on the individual requirements of staff. Self service reporting, enables an interactive reporting experience, as end users can make modifications and additions to their reports on the fly calling information to them instantly. Since report elements are chose individually, end users are able to ask their own questions of the data fully customizing their reports to match their data analysis needs. Additionally, end users should be able to interact with their finished reports by applying controls such as on-screen filters, sliders, conditional formatting, and by creating drill down and linked reports.
$$$ vs. $
One of the great benefits of Self-Service BI is the price, as well as further money that can be saved. With Self-Service BI being available over the Cloud, it can greatly reduce cost as no hardware need be installed. In addition to this saving, specific reporting staff are not needed as end users can report themselves, thereby saving money on personnel.
Standard Reports Vs. On Demand Reporting
Implementing ad hoc reporting functionality can be of major benefit to the entire enterprise. Self-service reporting puts the tools necessary to build a fully functional report and modify existing reports directly into the hands of end users so that data analysis can be achieved quickly, intuitively, and interactively with little to no training. Ad hoc reporting speeds the report creation process by empowering end users to work with their reports independent of developers. This helps to eliminate the lengthy back and forth cycle between end users and IT to achieve a final report, saving valuable time for both the end user and developer and allowing them to focus resources towards more mission critical activities. The platform gathers and stores all your cloud and on-premise info in a centralized location that you can access anytime, anywhere. You can also make use of pre-packaged content packs and built-in connectors to streamline import of your data from other sources (internet).
Dashboards and Reporting vs. Data Visualization as a service
An extensive library of visualizations and an intuitive drag-and-drop interface makes it easy for users to build data discovery dashboards. It will enable users to quickly visualize data with out-of-the-box grids, graphs, charts, and maps. If that’s not enough, it’s also easy to extend the visualization library to incorporate new third-party visualizations, like D3, or build your own from scratch with our Visualization Builder and SDK. Self-service tools allow them to visually slice and dice data, drill down to the bottom, and even change appearances with different chart types and a wide range of predefined templates for everyone. Visualization can change how business managers and other workers “see” data. The way data is presented to users will be as important as the information itself. But for achieving that, a flawless IT and BI architecture must be built that can deliver the right data to the right users and empower them to take advantage of it.
As an organization, you won’t get very far on self-service BI and data visualization if you don’t have high-quality data, a well-designed systems infrastructure, and consistent processes. A lot of work has to take place behind the scenes to build an IT and BI architecture that can deliver the right data to the right users and empower them to take advantage of it.
Making the transition to self-service analytics can be tricky and filled with challenges. Implementing few rules such as Embracing good data quality practices, Documenting Data definitions and lineage standards in data dictionary, embedding data science in reporting solutions, Developing security practices can will create a strong foundation for your team to build on. So, what’s next? Finding a trusted implementation partner can help. At NRoot Labs, our team of experts know BI and cloud computing. We helped many companies bridge that gap between IT and business users. Call us for a quick chat to discuss how you can bring the balance between IT and business at your organization.