Controlling the Data Flow
To be useful, data scientists must increase the accuracy, timeliness and amount of data, often weighing the speed of collection from the data warehouse with the quality of the data being collected. In fact, “data quality” was a top concern of survey respondents in All Things Insights’ most recent Analytics & Data Science Spend & Trends Report. As one contributor put it, data capture today is like a firehose being turned on, with the user unable to control the direction or volume of the flow.
The advancement of technology in data collection has made it seem challenging for the data expert to keep up. Just what to do with all this big data that is being captured? On the more positive side, data teams have become better and more agile in filtering out the data that they don’t need, thereby saving time and increasing reporting speed, improving accuracy, reducing costs—and increasing revenue by bettering business decisions.
It is improving and streamlining those business decisions that ultimately determines the success of business intelligence and data analysis initiatives. It helps the bottom line by helping management understand the data and to derive insights, identify problems, spot trends and find new growth potential. As IBM notes in its blog, “What is business intelligence?,” “Although business intelligence does not tell business users what to do or what will happen if they take a certain course, neither is BI only about generating reports. Rather, BI offers a way for people to examine data to understand trends and derive insights.” And it helps support decision making across the business, notes IBM, by:
- Connecting to a wide variety of different data systems and data sets including databases and spreadsheets.
- Providing deep analysis, helping users uncover hidden relationships and patterns in their data.
- Presenting answers in informative and compelling data visualizations like reports, maps, charts and graphs.
- Enabling side-by-side comparisons of data under different scenarios.
- Providing drill-down, drill-up and drill-through features, enabling users to investigate different levels of data.
The Future of Data
The best business intelligence software supports the decision-making process across the business, and can range from the most basic systems to advanced functions that use artificial intelligence. In All Things Insights’ recent article, “Unifying Data Analytics and Insights,” we asked the question, to be human or not to be human? That is a relevant question in today’s technology-driven society, and one we posed when thinking about unifying data analytics and insights along with the rise of AI, machine learning, and automation technologies. While there is no doubt that these fields will transform the insights space, very few of us truly understand their value and the challenges they will present to our industry and selves. The intersection of technology and methodology is happening, but it’s unclear what if any practical value they will hold in the future.
Speaking of data and the power of analytics, how do we start incorporating data translation and storytelling in our organizations in a more meaningful way? According to Neil Hoyne, Fellow at Wharton, in a conversation with Seth Adler, there’s a huge gap that is steadily rising. It’s not enough to just gather more data, of course. You’re also going to need to hire more data scientists to analyze all that new data. Hoyne attempts to address what’s holding certain companies back from milking the most out of their “big data.” For more on this discussion, visit All Things Insights’ blog, “Translating Data into Action.”
Business intelligence plays a crucial role in supporting the insights function. By providing data-driven insights, it empowers the insights function to make informed decisions, drive strategic initiatives, and deliver valuable recommendations. We asked ChatGPT for some specific ways in which business intelligence benefits the insights function:
1. Data Integration and Consolidation: Business intelligence tools enable the collection, integration, and consolidation of data from various sources within an organization. This comprehensive view of data allows the insights function to access a wide range of information, including customer data, market trends, sales figures, and operational metrics. By having a centralized data repository, insights professionals can analyze and interpret data more effectively, uncover patterns, and derive meaningful insights.
2. Data Visualization and Reporting: BI tools offer robust data visualization and reporting capabilities, allowing insights professionals to present data in a visually compelling and understandable manner. Interactive dashboards, charts, and graphs facilitate the communication of insights to stakeholders across the organization. By using visualization, the insights function can effectively convey complex information, trends, and patterns, making it easier for stakeholders to grasp and act upon the insights.
3. Advanced Analytics and Predictive Modeling: Business intelligence tools often include advanced analytics capabilities that enable the insights function to perform in-depth analysis and predictive modeling. By leveraging statistical techniques, data mining, and machine learning algorithms, insights professionals can uncover hidden patterns, identify correlations, and make accurate predictions about customer behavior, market trends, and business outcomes. This analytical power supports strategic decision-making, market forecasting, and proactive planning.
4. Real-time Monitoring and Alerting: BI tools can provide real-time monitoring and alerting capabilities, allowing the insights function to track key performance indicators (KPIs) and important metrics in real time. With access to up-to-date data, insights professionals can quickly identify deviations, anomalies, or emerging trends, enabling them to respond promptly and make data-driven recommendations. Real-time monitoring also facilitates agile decision-making and supports proactive adjustments to strategies and initiatives.
5. Self-Service Analytics: Business intelligence tools often offer self-service analytics features, enabling insights professionals to explore data, create custom reports, and perform ad-hoc analysis without relying heavily on IT or data teams. This self-sufficiency empowers the insights function to access and analyze data more efficiently, iterate on insights, and respond to changing needs and requests. Self-service analytics also fosters a culture of data-driven decision-making.
6. Identifying Opportunities and Risks: BI helps the insights function identify opportunities and mitigate risks by uncovering valuable insights from data. By analyzing historical and current data, insights professionals can identify market trends, customer preferences, and emerging opportunities. They can also identify potential risks and challenges that need to be addressed. This foresight enables the insights function to recommend proactive strategies and initiatives that capitalize on opportunities and minimize risks.
Business intelligence benefits the insights function by facilitating data integration and consolidation, providing data visualization and reporting capabilities, enabling advanced analytics and predictive modeling, supporting real-time monitoring and alerting, offering self-service analytics features, and identifying opportunities and risks. By leveraging BI tools, the insights function can extract actionable insights from data, drive evidence-based decision-making, and deliver valuable recommendations.
This data renaissance, if you will, dovetails perfectly with the renewed emphasis on data storytelling in corporate enterprises. After all, it’s not about the latest shiny object but is instead all about the understanding derived from the data. As Brent Dykes, data strategy consultant and author, “Effective Data Storytelling,” put it to MIT Management, “The skill of data storytelling is removing the noise and focusing people’s attention on the key insights.”
Video courtesy of Adam Finer – Learn BI Online