Benefits of Using Data Visualization With Data Warehousing

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Businesses gather a substantial volume of data from various channels, such as sales, customer interactions, and operational processes.  

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But having data alone is not enough to run a business for success. Making sense of the ever-growing mountains of data is a challenge that businesses of all sizes face today.

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What businesses absolutely need are streamlined processes and relevant sources that can help them efficiently store, manage, and present data for clearer, and more actionable insights.

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This is where data warehousing and data visualization step in. Using both can unlock valuable insights for strategic decision-making, enhance operational efficiency, and improve overall performance.

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Based on their crucial role in business success, let's delve into understanding data warehousing and data visualization, and how their combined usage enhances company performance.

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What Is a Data Warehouse and Why Do Businesses Need One?

A data warehouse is a centralized system that collects large volumes of organizational data from various sources to assemble and store it. It is designed to assist businesses in analytical and reporting activities, enabling businesses to make data-driven decisions.

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Through this singular system, businesses consolidate data from all sources, such as transactional systems, relational databases, and so on. It is periodically extracted from various internal applications like sales, marketing, finance, customer support, and external partner systems.  

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According to a recent report by Allied Market Research, the global data warehousing market is expected to reach $51.18 billion by 2028. Recent statistics by G2 also reveal that among IT managers and executives, 52% prioritize faster analytics as the most critical aspect of data warehousing.

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A data warehouse can facilitate the decision-making processes for businesses because it provides:

• Improved data consistency for informed decision-making.

• Streamlined access to enterprise data for end-users.

• An enhanced data documentation for better transparency.

• Lowered computer costs and increased productivity.

• Empowerment to end-users to generate ad-hoc queries without system performance impacts.

• A centralized collection of related data from diverse sources.

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This is because a data warehouse is:

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• Subject-focused: A data warehouse provides information tailored to specific subjects like product details, sales data, or customer profiles, rather than providing a vague picture of an organization’s operations.

• Integrated: A data warehouse consolidates data from diverse sources such as flat files and relational databases.

• Time-variant: The data in a data warehouse is categorized within a particular time, offering insights from specific historical points.

• Persistent: Historical data remains intact in a data warehouse, ensuring it's retained even when new data is added.

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Data warehousing makes the process of data visualization much easier and more effective as it is quite convenient to look for data (to be represented) in one centralized place containing a sole source of truth from all sources.  

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To better understand how, let’s move to the role of data visualization and learn how it helps in understanding data better.  

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What Is Data Visualization and How Does It Enhance Data Understanding?

Handling copious amounts of data can be overwhelming. This is where data visualization becomes essential.

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Data visualization can decrease your cognitive load by giving you a comprehensive evaluation of your data facilitating a more efficient and straightforward interpretation of complicated information. It might surprise you that 90% of the information entering our brains is visual.

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Data visualization involves using visuals such as charts, graphs, or maps to display data, simplifying complex or large datasets. It helps enhance and streamline visual communication, aiding in accuracy and detail. Visual representations help extract valuable insights from raw data, facilitating informed decision-making.

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Data visualization creates additional value to the existing data consolidated in a data warehouse. It helps yield insights pertaining to predictions in sales, market trends, and even changes in industry prices as per the changing market dynamics.

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Dashboards are a powerful tool for showing off your data's visualization. Dashboards are effective instruments for monitoring and displaying data from several sources, providing information on how particular team actions or the actions of nearby teams affect overall performance. They use standard visuals for visualizing data, such as:

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• Tables - Tables organize data into rows and columns for an easy comparison of variables.

• Pie Charts and Stacked Bars - These charts divide your data into sections, each representing parts of the whole picture. This makes it simpler to compare the size of each section.

• Line Charts and Area Charts - These charts display trends over time by plotting multiple data points. While line charts show lines to show these changes, area charts stack these data points and use colors to differentiate variables.

• Histograms - Histograms use bars without spaces to show the distribution of your data. This makes it easier to identify outliers within a dataset.

• Scatterplots - These illustrate the relationship between two variables.

• Heat Maps - These visualize behavioral data by location, mostly on a webpage or a map. This helps you highlight patterns in user behavior.

• Tree Maps - These display hierarchical data as nested rectangles, allowing categories to be easily compared through area sizes.

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While having all can help paint a better picture of your data, it's crucial to select the appropriate chart or graph that best matches the type of information being presented, as some are more suitable for specific types of information than others.

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For instance, if you’re a clothing brand and want to detect geographic locations where your brand performed the best, then a heat map would be ideal. Contrarily, if you’re someone from the SaaS industry and want to analyze the trends and fluctuations in your content, then a line graph is perfect for highlighting peaks and downfalls.

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Effective data visualization balances form and function. A plain graph might be too dull to attract attention, or it might deliver a powerful message, while a stunning visualization might fail to convey the right message or to communicate effectively. The key is for data and visuals to work together, and there’s an art to blending strong analysis with compelling storytelling.

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If you want to take a step further in your data visualization game, you can adopt data visualization tools to easily monitor and track key performance indicators (KPIs) and other critical metrics for success.

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Power BI and Tableau are regarded as industry leaders in the world of visualization tools as they are easy to use and have powerful data visualization capabilities.

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(To identify which tool would be best for your business, click here for a detailed comparison of Tableau and Power BI)

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Benefits of Using Data Warehousing for Data Visualization

Data visualization cannot operate on its own. To display and demonstrate vast amounts of useful data and information, you need a system that collects, aligns, and segregates information or data according to its nature.  

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Simply said, data visualization needs data warehousing for better information sharing and to enhance business operations through data-driven decision-making.  

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When used together, data warehousing and data visualization enable organizations to:  

• Improve the quality and consistency of data.  

• Optimize business processes for success

• Increase efficiency rate of organizational processes

• Identify new and unique market trends  

• Forecast upcoming problems  

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Companies That Are Using Data Visualization

Our words will start to make even more sense to you if we tell you that they’re backed by the world’s leading brands.  

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You guessed it right; we’re about to unveil to you how some of the world's best-performing branding uses data warehouses and why.  

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1. Spotify

Spotify uses data visualization to enhance user experience by notifying users about new releases and popular songs.

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Source: Review.org

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Their data visualization strategy shows users which songs are trending in real-time, helping them stay updated with the latest music trends. This enables the company to retain its users by making it easier for users to discover new artists and releases without having them spend extra time searching through different music platforms (such as iTunes).

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2. Amazon

Amazon uses data visualization to provide customers with a bigger picture of its inventory for its customers. This helps them make informed purchase decisions while searching for products to buy.

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Source: Invisibly

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For instance, when you visit a product page on Amazon, you can identify how many units are available and how many have purchased them. Amazon uses tools like Amazon QuickSight, a serverless business intelligence tool that offers interactive dashboards and analytics powered by machine learning for customers to make better purchases.

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💠 Case Study: Data Pilot enabled a large logistics company to achieve a real-time visibility into its operations

‍In one of its major projects, Data Pilot’s data warehousing and visualization services helped a renowned logistics company in Pakistan get a well-rounded outlook of its operations in real-time.

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The Problem

This logistics company lacked an analytics dashboard for the operations team to track and monitor its parcel deliveries, cash collected, and rider and vendor performance. They relied on manual Excel-based reporting, leading them to spend several hours on redundant tasks and limiting their time spent on finding new opportunities for growth.

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The Solution ‍

Data Pilot solved this problem by building an ETL pipeline and data warehouse, which allowed data from their operational data store to be pulled with ease based on their reporting needs. This dashboard was built to be automatically updated with new incoming data, enabling the operations team of the company to make prompt, data-driven decisions. This allowed the company to better serve the needs of their customers and provide them with an intuitive purchasing experience.

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Conclusion

While businesses gather substantial volumes of data from various channels, merely having data is not enough to guarantee success. For a business to make sense of it all and plan the next steps ahead, it is essential for it to have both data warehousing and data visualization in its strategy. By leveraging both, businesses can optimize operations, understand customer behavior, and quickly adapt to market changes, turning data into a strategic asset for growth and innovation.

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If you’re looking for a data services provider to give you a comprehensive view of your operational data and streamline your business processes, consider using Data Pilot's data visualization and data warehousing services to collect, store, manage, and present your data effectively.

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