Last month marked the culmination of 14 years since I began my professional journey post-graduation in a non-IT domain. Initially, I delved into tasks involving MS Excel for reporting purposes and utilised SQL for data retrieval. However, over time, I found myself caught in a repetitive cycle of writing similar codes and formulas.
It was during this period that a colleague introduced me to Tableau, as he was seeking to replicate Excel charts using this platform. While assisting him, I became deeply engrossed in Tableau, and it has remained an integral part of my professional toolkit for over a decade now. Since then, I’ve embraced this new direction wholeheartedly and have never looked back.
For many clients, utilising Tableau solutions resembles presenting an array of diverse cuisines on a single enticing platter tailored to their preferences and moods. In contrast to conventional reporting methods and platforms, Tableau stands out as a potent tool for visualising data sourced from multiple platforms, enabling users to engage with data through various chart formats. This facilitates expedited decision-making for clients and provides them with comprehensive visibility into data dynamics.
For a client new to Tableau, the journey commences with the identification of opportunities where Tableau can provide value. Subsequently, we conduct a gap analysis to evaluate data sources, their quality, and availability. This process lays the groundwork for defining the project scope and progressing towards its realisation. In certain scenarios, creating a prototype may be necessary to instil confidence among stakeholders and ensure alignment with their expectations.
Conversely, for clients with well-defined requirements, the initial step involves presenting the use case and outlining its benefits in relation to their specific problem statement. This is followed by mapping out the roadmap, encompassing considerations such as the necessity for an ETL tool, data transformation requirements, customised visualisations, and user permissions.
Regardless of the starting point, comprehensive discussions with the client are pivotal. These discussions delve into their business objectives, key performance indicators (KPIs), and precise data requirements. Such consultations often entail engaging stakeholders from various departments to gather diverse perspectives.
To maintain relevance in any job role, it’s imperative to consistently engage in learning and development efforts, ensuring both your organisation and clients can rely on your expertise. This commitment to ongoing improvement should become a disciplined practice, with continuous learning being a core principle. Some strategies I employ include:
Challenges encountered by organisations in adopting Tableau can vary significantly. Some of these challenges include:
To empower clients with self-service analytics and utilise Tableau for analysis, Beinex offers the following services:
For the Authority of Finance, our team addressed the challenge of manual reporting through the strategic implementation of Tableau. We successfully transitioned from multiple internal reports to a comprehensive BI dashboard, introducing a self-service analytics platform with the integration of Big Data solutions. Today, various ministries depend on this consolidated reporting repository for their financial analytics, contributing to enhanced operational efficiency and improved decision-making.
For a leading commercial bank in the UAE, we focused on refining their financial reporting processes. Our approach involved a meticulous storytelling strategy in conjunction with Tableau’s capabilities, resulting in the automation of key financial ratios. This transformation not only elevated user engagement with financial statements but also realised significant time savings through the deployment of automated, ready-made reports.
The leading telecom authority based in UAE posed a unique challenge in transforming its data culture and analytical ecosystem. Leveraging Tableau, we cultivated a self-service analysis culture, seamlessly connected disparate data sources and introduced predictive dashboards. The outcome was a substantial improvement in telecom coverage based on data-driven insights and a notable reduction in manual efforts through the automation of analytics.