Greater visibility and insights from data are no longer merely options for business competitiveness. They’re table stakes. Data gives companies the ability to understand and deliver exactly what their customers want, when they want it. Additionally, monitoring data streams can ensure product quality, alert operators to anomalies, and minimize production downtime. Businesses that don’t collect, analyze, and use data in their operations will find themselves defeated by those that do.
But not all of your clients have data analysts on staff or the computing power to perform big data analysis in house. To unlock the value of their data, your clients will need you to help them select the right data analytics tools.
Data Analytics as a Service provides subscription-based data analytics tools through the cloud. These solutions are often designed to democratize data analysis, allowing people in any role in the company and regardless of their technical expertise to have the ability to access and use insights from data.
There is a wide range of data analytics tools to choose from, which makes it possible for you to tailor a solution to your client’s needs. You need to be careful in your selection, however, to avoid the following pitfalls.
People in all roles with different skill sets to make data-based decisions. Data analytics tools need to be intuitive so everyone who needs them can use them. The data analytics solution also needs to be easy to launch. You may be able to eliminate complexity by choosing an end-to-end solution that includes all components of a business intelligence (BI) stack such as ETL (extract, transform, load), analytics and visualization.
Before vetting data analytics tools, narrow your choices to those that can accommodate the maximum number of users the company will have at any time and the volume of data they need to process. The solution should also have the capability to provide the answers your client needs within their expected timeframe.
Limited Data Sources
Some solutions support only one data source — others will analyze data from multiple sources. Make sure you have a thorough understanding of where your client’s data is coming from, the format the data is in, and that the data analytics tools you choose can handle it. If your client is using multiple data sources, make sure your solution makes integrating disparate data streams as easy as possible.
Make sure the data analytics tool you choose can visualize data effective for your client. You may want to choose a tool that lets you customize reports and graphics to present the most important information to the user in a way that’s easy for them to quickly understand. Some data analytics tool vendors offer industry-specific dashboards with their solutions configured for the metrics, key performance indicators (KPIs), and cost analysis that businesses in those verticals commonly need.
Businesses need to protect their data. When you are evaluating a solution for security, make sure it not only keeps data safe from hackers but also includes features that limit access to only employees who need the data to do their jobs. Your clients may also require an audit log showing who has accessed information. Some solutions also have the capability for administrators to hide certain data from shared dashboards based on the user’s role.
It’s also vital to ensure that the data analytics tool you choose is backed by reliable support. Research how and when users — and managed services providers — can contact support or submit a ticket and if there’s an additional cost for premium service with shorter response times. Also, investigate whether the vendor provides training and if you will have a dedicated contact that you can reach when you and your clients need them most.
The best data analytics tools for your client will improve, not complicate, their current processes by putting insights from data at their fingertips that they can use to make intelligent decisions to grow their businesses. Make sure you don’t implement a solution for your client that will interfere with the value data can provide to their organization.