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June 9, 2023
Mile Zivkovic
Are you sitting on a goldmine of data without realizing it? Find out today by doing data discovery - we’ll show you what it is and how to do it.
Have you ever tried reading a dictionary? All those words on their own in one place are impressive, but it’s far from a masterpiece like The Great Gatsby. The same goes for your data - just having it in one place at a time is good but does not tell you a captivating story.
To make sense of various datasets that your business collects, you need data discovery. Today, we’re going to show you what data discovery is, how to do it, and which tools you can use to get started. And don’t worry, you don’t need a team of data scientists to do any of what we’re going to describe.
Data discovery is the process of analyzing your data and finding meaningful patterns. Most businesses collect data from a large number of sources and in a plethora of formats. As a part of business intelligence, data discovery serves as a way for businesses to become more efficient, better understand their customers and their own business and in the end, make better business decisions.
There are two main types of data discovery: manual and automated (smart) data discovery. Manual data discovery means going through your datasets and manually trying to identify trends and patterns. Automated data discovery means using automation tools to find meaning in your data and is the preferred method for many businesses.
Data is all around us and no matter what type of business you run, you’re going to work with business data in some shape or form. Smart data discovery is the first step in making sense of that data and using it for business advancements. Here are some data discovery use cases.
First, you can analyze and refine your internal business processes. You can spot inefficiencies and learn where you need to spend more, work smarter and what to eliminate.
Second, you’ll have more data about your customers - who they are, how they use your product and what they spend time and money on.
Third, you can save money by analyzing where you have the best return on your investment. You can also find out which types of customers bring the most value to your business, and adjust your tactics thanks to predictive analytics.
Last but not least, your business can become more secure and compliant as data discovery helps with data protection regulation. Proper data discovery is the beginning of protecting your (and your customers’) data and complying with international regulations and data governance laws such as GDPR.
Whether you do it in an automated or manual way, data discovery is an iterative process that has similar steps. It’s worth noting that companies that deal with a lot of data discovery and data exploration may need a dedicated data product manager who is in charge of the data catalog for their business.
First, determine what you want to do with your data. Do you need to spot trends in your paid spend or find out how much server bandwidth your customers are using up each month?
Once you identify your needs, you’ll know the different sources you need, as well as what kind of tools and processes you should employ.
In the first example, you’ll need to pull paid ads data from all the platforms where you run ads. Think Facebook, LinkedIn, Instagram, Google Ads, and others. To successfully complete this step, you’re going to need a data discovery tool that supports all of your desired sources and data formats.
The process of cleaning your data means deduplication, proper formatting, adding missing fields, removing errors and outliers, and making sure that data from various sources is displayed in a correct, uniform way. This data preparation is crucial if you want meaningful results from complex data later on.
Having numbers on a page can lead to actionable insights and improved decision-making. But it’s even better when you visualize that data so that it’s easier to understand and learn from. All of your stakeholders and especially your customers will benefit from data in a visual form. This is why it is better to use a process flow diagram and other visuals to explain complex information rather than relying solely on textual explanations or spreadsheets.
Most of the tools we’ll mention in a minute support a variety of data visualization types: graphs, pie charts, bar charts, histograms, Gantt charts, scatter plots, and others.
Now comes the fun part - the discovered, cleaned, and visualized data is going to tell you a story that you can learn and benefit from. For example, you could unearth that you’re severely overspending on one platform compared to the rest with no significant return on investment.
With the analyzed data at hand, you can save it (e.g. in a data warehouse) and keep it handy to refine your business processes, optimize your spending, get new tools or change your existing ones, start pursuing a different type of customer, and more. The insights you get can change the way you run your business for good.
The average business today collects a large amount of data. From your customers, website visitors, internal team members, and other stakeholders, through a variety of apps and platforms. To make sense of it, you can try these tools - most of them will not require any knowledge of data science to use them proficiently.
If you’re looking for advanced analytics and data visualization for SaaS, you just found it in one place. Luzmo is built specifically for SaaS and it blends right into your product as a functional dashboard for your customers.
It helps you collect your product data and using our advanced analytics API, it pulls that data and creates interactive, self-service dashboards for your business users. It’s easy to set up and thanks to highly customizable designs, it fits right into your product as a fully white-labeled solution.
And with data access at their fingertips, your customers can see the value of your product even more clearly.
If you’re looking for an enterprise-grade solution for data analysis and data management, Tableau just might fit the bill. With its desktop and server tools, it allows for connecting a variety of data sources and doing real-time data discovery and visualization.
Its primary use cases are reporting and data analysis - if you want to use it for embedded analytics, you might find it cumbersome and expensive. However, its vast number of data sources and tight security make it a good choice for in-house data discovery. Another use case is as a project management tool, making it an alternative solution to Asana, for example.
It’s hard to mention Tableau without its nemesis and biggest competitor, Power BI. Microsoft’s tool helps with all stages of data analytics, including discovery, reporting, and visualization. It includes a wide range of tools for data insights, such as Power BI Desktop, Power BI Pro, Power BI Mobile, Power BI Embedded, and others.
Its strength lies in the variety of different visualizations, real-time analytics as well as Azure machine learning integration. However, its embedded function is pretty complicated to use compared to some other entries on the list.
If you like Tableau and Power BI but want something more cloud-based and powered by artificial intelligence, this is a great alternative. Use it for your big data analysis and smart visualizations that are on par with its pricier competitors.
No matter what kind of business you run, data discovery is a smart move to get the most relevant data for your business in one place. With better control of your data, you can control your business outcomes, increase revenue and make your customers happier with your product or service.
And if you run a SaaS product, doing data discovery, analysis and visualization has never been easier. With Luzmo, you can create interactive embedded SaaS dashboards in hours, not weeks or months.
Experience the power of Luzmo. Talk to our product experts for a guided demo or get your hands dirty with a free 10-day trial.
