It’s easy to get lost in the mass of information that comes in and goes out of a business. Combing through key data to pick what propels your business goals and evaluating how that data enables you can be a challenging task. Whether it is to look back at what happened (descriptive analytics), why it happened (diagnostic analytics), what is going to happen (predictive analytics), or to determine the next best course of action (prescriptive analytics), a business has a wealth of intelligence to rely on.

So, if you’re looking to tap into the bounty of data analytics and optimize it to meet your business aspirations, here are 5 questions to ask!

1. 1. What are my goals?
      Similar to starting a research, you must know your research goals and be equipped with “research questions” that’ll enable you to explore the depths of the subject matter.
      • What are you trying to solve?
      • Which spectrum of the data analysis journey (descriptive, diagnostic, predictive, prescriptive) will you be delving into?
      • Which aspect of your business deserves priority with data analytics?
      • What is the financial allocation for your data analytics efforts?
      • Do you have a team with the right mindset, ready to implement the project, and champion its success?
        
        

      These are all questions worth considering. Whether it is to increase brand visibility, grow sales, boost operational efficiency, improve financial forecasting accuracy, or predict various business shifts, your business’ stakeholders must get together to explore what your objectives are, and what you are trying to achieve.

   2. Do I have the resources needed to implement data analytics?
      Before kickstarting the process, you must know what data is available for you to analyze, and if you have the requisite team to carry out the project. Data can vary from customer demographics, website traffic, sales figures, risk and compliance entries, human resource records, and more. Furthermore, the analytics technology of your choice must have access to the data you are trying to obtain. This step will require the collaboration of your company’s IT team and functional subject matter experts. Ensure time-consuming setbacks are avoided and that you have the right team to guide you to identify the needed data.
      
      

      The success of your analytics endeavors heavily relies on the data architecture that is chosen; this will act as the blueprint of the project. It also depends on the data architects and those who will act on the architect’s directives. Data engineers, analysts and subject matter experts must work together to create a well-rounded team for the project’s success. Having an internal team of experts is a valuable asset. If you don’t, it’s worth considering hiring an external partner with the necessary skills and experience!

   3. How would different people in my company benefit from data analytics?
      According to Gartner, by 2026, 65% of B2B sales organizations are to transition from intuition-based decision-making to data-driven decision-making. In other words, from the top of the executive leadership to frontline employees, data analytics is paving the way for everyone to work smarter, more effectively, and with specific intent.
      
      
      • Enabling the C-suite to frontline employeesNot only does data analytics enable the C-suite to make informed decisions or identify new business opportunities, but it also benefits the management level, providing insights into departmental performance and how to optimize day-to-day processes. Frontline employees such as sales representatives or customer service agents can use data analytics to identify best-selling products and adjust their pitch accordingly.
        
        
      • Providing insights for data scientists
        By harnessing the power of machine learning, they can build models to predict future trends or identify insights that may be challenging for a human to discern. This will open a realm of possibilities empowering organizations to make decisions guided by foresight rather than as reactive measures. With this level of data availability, your company can observe patterns, delve into historical data and even create customized experiences.
        
        
      • Supporting those responsible for conveying insights

        It’s important to note that insights should be comprehensible to stakeholders so that they can be put to maximum use. For such reasons, data should be presented in compelling ways through dashboards, visually intuitive reports, or scorecards that provide assessments of daily goals with details on progress, obstacles and achievements.

        Your teams can tap into various tools such as Power BI to translate data into actionable insights. Drill down and understand for yourself even more than what the dashboard shows, explore data at a granular level and gain deeper insight into the data of your interest. This self-serve model can even encourage non-technical users to explore data and derive insights, reducing the reliance on data experts.

        Take it a step further by leveraging AI to significantly expedite the generation of meaningful insights. Eliminate the reliance on manual efforts to have AI analyze vast datasets, and unravel data stories in front of you that you never thought possible.

   4. Which trends and technologies should I consider?

      Your data analytics journey requires you to evaluate numerous tools, technologies and trends so that you make the most suitable choice for your business. According to recent research data volumes grow on average by 63% per month; so there’s a lot to work with, and a lot to learn.

      • Data lakehouses – are a direct response to this anticipated future. A data lakehouse provides the flexibility of a data lake where organizations can ingest and store large amounts of raw and unstructured data, as well as structured data with a predefined schema as done in data warehouses. This allows businesses to consolidate all data into a single source of truth, generate different types of analytics, as well as obtain insights in real-time.
        
        
      • Modern BI – helps users access and share data from anywhere, at any time, and almost through any device. This includes self-serving their own insights, and enabling employees to create compelling data stories.
        
        
      • Generative AI and copilots – the latest for analytics within the AI buzz, copilots are generative AI assistants that you can use to ask questions based on your data and receive answers through self-generated dashboards.
        
        

      As technology advances and trends shift, navigating what’s best for your business can also become increasingly complex. It’s best to devise your strategies with experts to make sure you’re on the correct path but also to make sure you are equipped with the most pertinent technology. For instance, incorporating services like Microsoft Fabric, an end-to-end analytics solution, can significantly enhance your data analytics capabilities, and make sure you stay at the forefront of technological advancements.
      
      

   5. Who’s in charge?

      By now, we’ve understood that the world of data is immense with layers upon layers of complexity to pierce through. That is why the data analytics journey isn’t only about tapping into these insights but also the organizational habits and discipline that enable a business to access the real-time, clean and relevant data it desires. This is known as data governance, and it is a responsibility that should be embraced by everyone within an organization; from data analysts to the C-suite executives.

      Data governance makes sure that data is treated as a valuable asset, and that it is maintained with accuracy and used ethically.
      This also includes the data security component that is not only important to your business but its customers, partners and other stakeholders who have entrusted you with their information.

      Well-defined data policies are an organization’s guiding principles for data security.
      A framework for data collection, storage, usage and disposal will facilitate a secure system that safeguards sensitive information from potential breaches. Learn more about why data governance is a crucial component of your data strategy.

      While it’s important to acknowledge that data governance is everyone’s responsibility, analytics can also benefit those who play a crucial role in directly governing the data of your business.
      Your IT and data infrastructure teams, as well as the legal and compliance teams, are all a part of this ecosystem that comes together to ensure your business is abiding by policies, communicating information with relevant stakeholders and operating in accordance with legal requirements. Analytics can be used by these individuals to function with utmost efficiency.

2. The way forward with data analytics

   When you embark on your data analytics journey, rely on an expert who can engage with your company to deliver tailor-made analytic roadmaps. Together you can explore how to set up a unified analytics platform and leverage the capabilities of advanced analytics and AI to unravel the full potential of your data. They should be equipped with the expertise to:

   • Outline long-term solutions that drive business value.
   • Assist you with automation for speedy processes.
   • Guide you on how the new data landscape can be adopted across the organization.

   
   Find out how Fortude has helped customers with their data analytic ambitions by clicking here.

   Don’t forget that data analytics can be an iterative process.
   However, by focusing on these 5 questions, you are sure to set a strong foundation. The data that is freely available in your systems can be the insights to help you blaze a trail and outshine the competition. Your next big idea might just be lurking in the unexplored depths of your data. Be sure not to miss it.