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The process of analyzing big data

The process of analyzing big data to improve your business operations doesn’t stop at purchasing data analytics software. If you want to achieve your goals, you should also put some elbow grease into learning the ins and outs of your new data analytics system. Moreover, it is pertinent that you have a clearcut idea of how to use it to your advantage. To guide you, here are some ways you can maximize your data analytics software:

  1. Define What You Want to Achieve Using Data Analytics. Even before purchasing your data analytics program, try to list down what you plan to use it for. Understand what aspects of your operations will benefit from using data, specify the type of insights you would want the platform to provide, and determine what you want to measure. By doing so, you will be able to specify your KPIs and other metrics as well as establish a good framework as to how you can use your new investment.
  2. Determine Where to Source Your Data. Most analytics platforms have the capability to source data from multiple internal and external systems for a more convenient data collection and synchronization process. However, this doesn’t mean you should simply integrate your platform to all your existing business systems and call it a day. Be selective about where you source your data, choosing only those that will help you move your data analysis efforts forward. This way, you not only generate more targeted reports but also prevent your database from being cluttered by information that you won’t even use.
  3. Regularly Assess Your Data Models. You wouldn’t use outdated information to perform analysis so why should you utilize outdated data models? To prevent old data models from having a negative effect on your data analytics efforts, you need to make it a point to assess these models every now and then. Check if you are ignoring certain data sources or if you have overlooked how certain fields could affect your model. Perhaps, there are certain data sources containing poor naming standards that are affecting your data analytics model. By taking this extra step, you can ensure that you are generating accurate reports that can drive your business forward.

By taking advantage of these tips as you implement your data analytics software, you are only a few steps away from reaping all the benefits that this technology has to offer. Hopefully, our list of 20 best data analytics tools was able to guide you in finding the right platform for your operations. To sum it up, we highly recommend choosing Sisense as it offers a code-free self-service analytics system that is great for users who don’t have the extensive technical know-how. Furthermore, it offers highly customizable dashboards, allowing it to easily adapt to your business’ data analytics and visualization needs. You can sign up for Sisense free demo here.