Everyone is talking about data. Whether it’s big data or small, simple or complex, freely accessible or locked up in spreadsheets, everyone is worrying about how to get their hands on it.
Many companies these days are scrambling for data to help inform their decisions. Buying a data tool and building charts isn’t the right way to solve the data problem. Data access is only a part of the problem. A company needs to know where and what to aim before they can find the analytics tool that hits their target.
To help companies pinpoint the right analytics tool to use, here are a few questions to ask yourselves as you begin to explore analytics software:
What questions are you seeking to answer, and what do you expect to accomplish with the results?
Before you can begin investigating your data , you need to define the problems you aim to solve. A good first step in choosing a data tool is to make a list of a few clear, quantifiable questions that you are expecting to answer with your data. From there, examine your needs and consider a few things:
- Do you need constant updates to architecture or will queries run a standard way?
- Do queries pull from a static data model or one that constantly changes?
Once you’ve got a good idea of the way you’ll use the platform, you need to examine your data sources.
Where is the data?
Making a decision about a warehouse solution is a crucial first step in finding insights that affect the entire company. From that single source of truth, data analysts and scientists can dive into the data and look for any connections that deserve investigation. When selecting a warehouse, keep in mind that queries differ in complexity and some data sources migrate easier to certain warehouses. Once you’ve mapped out the flow of data from native sources to a single data platform, it’s time to start thinking about the humans who will interact with the data.
Who handles the data?
Before you can make a decision about a data analytics tool, it is important to develop a clear understanding of the people who will be using that tool and the types of work they’ll be doing with it.
Different teams handle their data differently; some begin the process with IT personnel, others with data engineers and analysts. To make matters even more complex, some companies change their data handling as they scale.
Sometimes several individuals or groups of individuals collaborate on data sets simultaneously in the analytical process.
Who consumes the data?
Once the data has been combined and formatted for analysis, it will end up in the hands of a decision maker who can use it to make tactical decisions. These final data consumers are also an important part of the tool selection process. If they receive information that they can’t use or understand, then the entire process is useless. Determine in what format these consumers need information, how sophisticated they are at reading data and how often they need analytics delivered.
What is the budget?
Data analytics tools are like most products — you get what you pay for. With a heavy investment in a tool, you need to consider the degree of customization that you will have. It’s always better to get something that fits your needs and can adapt as your company grows to involve more data, more data handlers and more data consumers.