Guest Post by Mozart Data
August 24, 2022
Business leaders choose to invest in data tooling — like a mobile-first business intelligence (BI) tool — because they’re excited by the prospect of achieving more impactful insights and visualizing data without having to dedicate as much time to it.
BI tools are absolutely a vital part of a company’s data stack — but their value can quickly be limited when data is unorganized and unreliable, because they aren’t designed to tackle that specific problem. They aren’t meant for storing and cleaning data. That’s why you need to make sure you have the data infrastructure and organization in place to make the most of your investment in a tool like Zing.
Let’s take a look at where your useful data actually comes from. Some of it is created internally, in your own systems. You’re likely tracking activities on your website, in your app/product, or in your inventory.
There are also the many external tools that hold enormous quantities of data. When your sales staff updates an account in Salesforce, you’re creating new data. When your marketing team sends an email via your CRM (like Hubspot), you’re creating new data. Ad platforms, social media platforms, and Google Analytics have data you need. You’re probably accumulating data from some source in CSV files still.
Having access to so much data is great, and for some analysis you can just work directly in the tool’s built-in reporting features.
But what about complicated analysis? What about automated reports and dashboards that your team can quickly reference in the course of focusing on their core job duties? For that, you need to get that data, siloed in many sources, combined and organized. That’s where the modern data stack comes in. It provides you with the data tools needed to extract data from those sources, load it into a data warehouse, and transform it so it’s ready for analysis.
This is critical if you want your data to be reliable. Centralizing your data and then utilizing data transformation is how you can go about “cleaning” your data — removing duplicates, accounting for inconsistent naming conventions, correcting manual entry errors, spotting suspicious outliers, and more. You can do this manually in your BI tool, but it’s not an efficient use of time.
Getting your data synced and clean is an enormous step — and it also opens up exciting new possibilities. You can start to combine data from different sources for specific uses. Your sales team might want to know how different cohorts of leads are behaving, and now you can more easily track the actions of leads from different sources and how they’re interacting with marketing and sales emails or calls.
With a modern data stack, you can automate this entire process, so your data is always up-to-date, accurate, and organized in a way your team knows how to work with.
If you’ve implemented a modern data stack and have taken the steps to make sure your data is organized and ready for analysis and visualization, a tool like Zing can become incredibly valuable. You want to make sure the data you’re referencing is reliable before checking on a report on the way to a sales meeting or in the middle of a conference call.
And with your data in great shape, more members of your company can stat utilizing it in their day-to-day, even if they don’t have strong technical skill sets. You don’t want to depend on your busy data analyst or bothering engineers because someone who needs data can’t actually use your tools. With the right data tools in place, you can democratize data and start building a data-driven company culture by making it easier for everyone to ask questions.
If you’d like to learn more about the modern data stack, you can schedule a demo with Mozart here or chat with someone on the Zing team about how their customers are organizing their data to get the most out of their tool.