QuotaPath Implements an All-in-One Data Stack and Starts Leveraging Data Across the Organization
The Start-Up's Guide to a Modern Data Stack
The Right Time to Build a Data Stack
The data your business collects from third-party sources is one of your most valuable assets and has made it possible to change the way that business is done the world over. With access to the right data, you can make business decisions that are rooted in real customer behavior and fact-driven expectations.
However, raw data is typically quite opaque and most people simply do not have the foundational knowledge to parse it on its own. That’s where business intelligence (BI) tools come into play.
Trying by hand to turn raw data into the kind of visualizations a BI tool can provide can take an incredible number of hours that can be better spent elsewhere.
A reliable business intelligence tool allows you to create visualizations from your raw data so that you can see what all the numbers actually mean at a glance and make your data-driven business decisions from there. BI tools allow your team to track performance against key metrics, inform strategic decisions, and share information across your organization.
There are plenty of options to consider when choosing a BI tool, but you may want to consider some of these features:
Data Visualization — Data visualization is a key component of most BI tools, but it is worth taking into account exactly how you plan to utilize your data before selecting the right tool. Some teams, for instance, may need to create stylized and branded visualizations for investors or clients while others may use data strictly internally. Prioritizing the specific tasks that will add the most value to your data landscape will help you choose the right BI tool for your team.
User Interface — A BI tool can be an effective way to allow every team usable access to business data so that it does not stay locked away behind the opacity of its raw form. When selecting a BI tool, be sure to find one that the users who need and want access to visualization capabilities can actually use without too steep a learning curve.
Permissions — While the number of seats and permissions can impact the cost of a BI tool, it can also have data security implications. You will want to choose a tool that allows you to give teams access to the data they need to do their jobs while protecting customer data and other sensitive information.
The unprecedented volume of data that businesses are collecting today is the result of using many, many different tools that each collect specific data points. For instance, if you are engaged in email marketing you are probably collecting data about open rates and click-throughs. If you’re spending on google ads or social media advertising, you have clicks and impressions to track, not to mention costs.
Where a BI tool can turn all that data into compelling visualizations, it has to get access to the data first, which is why your data warehouse and business intelligence tools go hand in hand.
As an introduction to data warehousing and business intelligence, a data warehouse can help you collect data from a huge range of sources and make it ready for your BI tool to parse. A tool like the Snowflake data warehouse allows you to consolidate data from many different sources, clean it, and combine it however you need for actual analysis. You can query this data and organize it into relevant tables that you can then reliably load into your BI tool, ultimately making it much easier to analyze. Because a data warehouse can keep all data — current and historical, from every tool and every physical location — centralized, it becomes critical in data-driven decision-making.
Choosing a data warehouse can be an important early step in any data-driven business strategy. As with BI tools, there are plenty of serviceable data warehouse options to choose from, but the following are some of the more important features to consider when comparison shopping:
Investment — Of course implementing a data warehouse is going to mean investing in the software. However, the investment goes well beyond whatever the monthly cost you are quoted. Choosing any new software includes investing the time to implement it and investing the people power to do the implementation and learn the software, all of which are costs worth considering before choosing one vendor over another.
Ongoing costs — The cost of supporting a data warehouse does not end at implementation. How many and what kind of people will be necessary to truly leverage the features of your new data warehouse? Take this cost into account when calculating the true cost of a new data warehouse provider.
Support — Your data warehouse can quickly become a critical part of your data infrastructure, meaning that at some point or another you are likely to run into a question or a problem. Finding a data warehouse that has easily accessible answers, including a responsive customer support team can be a huge help when issues occur.
Above all, you’ll want to select a data warehouse tool that meets the needs of your business and will be able to grow with you as the volume of data you collect inevitably grows, too.
Business intelligence tools can be quite powerful and help you gain insights into many different aspects of your business. But like so many other pieces of software, you can only get out of a BI tool what you put into it. A business intelligence framework or business intelligence strategy is vital if you hope to understand and fully leverage your company’s data.
One place to start with a business intelligence strategy is by investing time and effort into your business intelligence architecture and its components.
So what is business intelligence architecture?
Business intelligence architecture is a foundational piece of your business intelligence strategy that provides a blueprint for how your company will collect, analyze, and leverage data. From a holistic view, business intelligence architecture typically includes:
A comprehensive understanding of your data sources: which data sources do you want to use? Are they already in place or are you planning to invest in new tools?
A strategy for collecting and verifying your data: where are your data sources currently storing your data? Do you need or want access to historical data from these sources? Is the data you’re collecting clean?
A data warehouse or other data storage plan: how can you ensure that data from multiple sources is accurate and able to be compared?
A BI tool or other plan for data analysis: how will you visualize and analyze your collected data?
A plan for data governance: how is data used, stored, organized, and disposed of?
While not every business will have a data intelligence architecture that looks exactly the same, these components are universal. By working through each one and making informed decisions about the tools and processes you will use, you can avoid a lot of wasted time and expense.
You can build out a comprehensive business intelligence strategy based on solid business intelligence architecture. As the different components start to come together, you will be able to see where you need to spend more time and attention. The complexity of putting together this kind of architecture should make it clear why businesses need a business intelligence strategy: there are simply many moving parts that each require planning to get right.
Both data warehouses and business intelligence tools can support your business intelligence strategy. Some other tools to consider when developing your business intelligence strategy might be an ETL tool, a data transformation tool, or a comprehensive modern data platform like Mozart Data. By building a toolkit and strategy around your data from the point of collection through to data visualization and decision-making, you will be constructing your business on a strong foundation from the start (or from whenever you get serious about your data solutions).
As you construct and refine your business intelligence strategy, you will want to have a reliable data warehouse in place sooner rather than later. The earlier you can start collecting clean, usable data and turning it into actionable insights, the better off you will be in the long term.
Setting up each piece of your business intelligence architecture separately can be quite costly, both in terms of capital and in hours. That’s why Mozart Data offers its customers a modern data stack that simplifies the business intelligence architecture process. Connecting your data sources to the Mozart Data stack allows you to have a centralized space to scrub, transform, and organize your data before syncing it with your BI tool. Mozart Data has partnered with Snowflake as our data warehouse provider since we know Snowflake is secure, flexible, and easy to use.
Contact us to learn more and schedule a demo.