Getting the Most Out of Cloud Analytics

Analytics is a critical component for many organizations that want to make sense out of their data. Taking your analytics to the cloud opens up many possibilities, but are you truly getting the most out of your investment?

Here are several tips to help your organization evaluate whether you have more opportunities for optimization.

Driving Buy-In and Adoption of Cloud Analytics

Do you have cloud analytics support available from decision-makers, end-users and other important stakeholders? If you have a lackluster reception to your cloud analytics initiatives, it can be difficult to access the resources needed to get the most out of this technology.

If cloud analytics benefits and functionality are unclear to the front-line people using the applications, then they may be tempted to use alternative solutions. A substantial change management plan can guide these groups into using all the capabilities that are available to them.

Understanding Cloud Analytics Solutions

Is your current cloud analytics solution the best one to support your organization over the short and long term? You have many choices available and sometimes the first one you select can fall short.

Gain a thorough understanding of the cloud analytics market, your organization’s unique requirements and consider talking with an experienced service provider about their recommendations. Check in with the data team to see whether they’re missing out on crucial capabilities that could take your analytics to the next level.

Choosing the Right Data Stores

Much like a mismatch with cloud analytics solutions, the data store your organization uses can also have an impact on your effectiveness. The databases, data warehouses and data lakes that house your data may need revisiting over time. Some organizations may use the data stores they’re most familiar with, while others will seek out options that maximize performance for their use cases.

The speed of your analytics can play a big part in which datastore works best. For example, if you have real-time analytics needs, then you need a high-performance data store that can keep up with these requests.

Supporting Ad Hoc Analytics

One big advantage of flexible cloud analytics solutions is that they often support ad hoc analysis. Your data team and other business intelligence staff can run reports outside of pre-programmed options, allowing them to answer new questions and connections.

Ad hoc analytics can uncover insights that your organization never had access to before. It also helps you use more of your available data, as some data types may not be represented in the standard reports. You end up with an analysis that’s customized to your organization, which helps you build upon your efforts going forward.

Opening Up Analytics Access

Your data team is not the only one that benefits from access to analytics insights. Many staff can benefit from having this information guide their daily decision-making. This type of operational analytics removes the delay between generating insights and getting them to the people who can immediately apply them.

A typical analytics workload may involve non-data teams spending a lot of time waiting to get reports. They could miss valuable opportunities and lack the information needed to make the most effective choices. Operational analytics can deliver insights into the software that staff is already using, making it a convenient way to make data work for their needs.

Application Modernization

Are the analytics solutions you’re using optimized for the cloud? Some organizations may lift and shift their current software into the cloud with limited changes. The analytics tool may have been developed without the cloud in mind.

In this situation, the analytics solution may not harness all the capabilities available in the cloud. It could fall short on access, availability and flexibility. Older applications may need to be refactored or even retired, depending on their suitability for your current and future needs.

Creating a Data Culture

Sometimes, your cloud analytics solution is excellent, but the results still don’t match your expectations. Your company culture may need to shift to a data-centric approach. Since data is so important in the modern business world, thinking about how it fits into your organization is critical. Your policies and procedures should center data first and foremost, whether that involves data governance as a whole or how data is collected in your organization.

Centralizing All Data

Your analytics solution can only work with the data that you provide. Is your organization set up with a centralized data store, or is it spread out across multiple silos? You may need to go through a thorough audit to ensure that your data ends up in the right place. Data pipeline solutions such as Extract, Transform, Load (ETL) tools can streamline this process.