When it comes to big data, data science, and data analytics, we often hear “store everything, analyze everything.” Though we believe that this view is correct, it is much easier to say than it is to do.
There are many questions that need to be answered when considering a comprehensive analytics solution. Here are just a few:
How am I going to connect to my data sources?
What is my data warehousing strategy?
Who is going to build my data model?
SQL? OLAP? Hadoop?
How will I maintain my infrastructure?
Can I be sure my system is secure?
How am I going to create value-added metrics, KPIs, and advanced analytics?
Do I need a separate presentation layer?
Who is going to build my visualizations and dashboards?
What happens when I need to make a change?
If this sounds complicated, that’s because it is. One option for finding answers is to hire developers, data scientists, and analysts to write custom code and cobble together some of the many tools that address one or two of these questions, but that is expensive, time consuming, and risky. Another option is to settle for a product that only answers one or two questions, like visualization, data integration, or reporting tools, but these are only interim steps that are not capable of providing complete solutions.
Fortunately, there is a third option. Analytics-as-a-Service providers like Actus Data take care of all the heavy lifting so you can focus on your business. We offer connections to a long list of data sources, custom data models, a powerful and flexible analytics infrastructure, pre-built and ad-hoc analytics, and configurable dashboards, visualizations and reports. On top of that, a subscription-based approach to data and analytics lowers the upfront cost and risk, dramatically shortens the timeline to generating value from your data, and gives you greater flexibility as your needs change. You are able immediately reap the benefits of domain experts without having to worry about specific skill-sets or new hires and all of that adds up to an attractive ROI.
After all, the reason you are storing everything and analyzing everything is not to become a data analytics company, it is to drive insights that improve results. Isn’t it time for you to stop worrying about all the details and to start transforming data into action?