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ANALYTICS SPOTLIGHT

What to Look for in a Cloud BI & Analytics Platform

The data landscape is quickly changing as companies ditch legacy solutions in favor of more modern, cloud BI and analytics platforms. Choosing the right solution is paramount, but with so many vendors on the market, how will you approach the buying process, set goals, and compare solutions?

It’s important to get a good idea of what you need from your cloud analytics platform. Every company is unique, and needs will vary. We recommend evaluating internal requirements and aligning purchasing decisions with those goals. It’s also important to note that not all BI tools are the same (or solve the same problems). Often, companies will deploy multiple tools for different use case, teams, or business units.

With that in mind, here are some guidelines to consider when selecting an analytics tool.

Take a User-Driven Approach

Remember that you’re building a solution to meet the needs of the business and analytics experts at your company. That’s why we suggest taking a user-driven approach. Is this solution for a specific department, or will people across the entire company be expected to explore data and generate insights?

In the past, data analysis sat in the hands of the data team, technical analysts, c-suite, or ran off Excel. But that’s all changing as more companies seek to make data a bigger part of their culture, keep data fresh and secure, provide access to massive data sets, and aid better decision-making. The rise of self-service analytics now make it easier to get data in the hands of any employee. These tools tend to have shorter learning curves and can be set up to meet the needs of people without a background in data science or extensive analytics training.

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Buyer’s Guide: Building a Cloud Analytics Stack

Considering a cloud analytics stack? Read our complete 2019 Buyer’s Guide.

Determine User Engagement

Consider how you want people to engage with data. If you expect domain experts in marketing, sales, finance and other departments to use your analytics solution, you’re going to need a self-service tool that allows business people to explore and query data without a background in SQL. Tools like Sigma empower business experts to ask more of their data without writing a single line of SQL, opening up big data queries to users outside of the data team.

Encourage Collaboration

If you discover insights, and you have no way to share it, does it make an impact? When it comes to BI communication and collaboration are key. But both are difficult with legacy analytics tools due to rigid licensing models, antiquated sharing tools, and dead-end dashboards. When looking at a modern cloud solution, keep collaboration in mind. Not only should it be easy to share reports and embed dashboards, but consider how easy it is for teams or coworkers to build upon each other’s analysis in the analytics tool itself. Being able to see the analysis your coworkers create and the data they reference lets you build on the base that someone else has created. This generates analytic compound interest, where one insight can quickly lead to others. It can also ensure multiple teams remain on the same page and share common metrics. Ultimately, collaboration helps surface the most useful insights without locking people into predefined questions.

Keep Adoption in Mind

It’s hard to create a data-driven culture if analytics applications aren’t easy to use or pricing models impede adoption with burdensome upfront costs. More and more enterprise software tools are moving away from buttoned-up interfaces in favor of simple, modern design that is intuitive and easy to use.

Cloud pricing models have also become more common. Companies are tired of paying for what they don’t use, and with the cloud they don’t have to. These features encourage organizational adoption in ways legacy tools have failed to deliver. Look for these features when considering a cloud analytics application. It will help make it easier to drive adoption and ensure data becomes a central tenet of your company’s culture.

Components of a Cloud Analytics Tool

Built for the Cloud

Most analytics tools available today have some form of cloud offering, but few are built for the cloud from the ground up. A move towards a fully-managed cloud solution makes sense at this stage. Why? The cloud-first data stack has finally reached maturity, and the constraints of on-prem or hybrid solutions hold back growing companies as they look to data to make smarter business decisions. You want to take advantage of the cloud benefits such as elasticity, real-time data access, sharing, and usage-based pricing.

Flexible Data Modeling

Analytics tools usually have built-in data modeling capabilities. But few products provide data admins with a flexible way to guide people’s data exploration and build centralized data definitions without holding back the business teams reliant on the insights.You want to balance control with the freedom to let business users find, add, and trust new data when completing an analysis. Otherwise, business experts can wait days or weeks for the data team to make model changes—which often causes them to go around the data team, download data extracts and use tools like Excel. This can introduce additional risk and make it hard to comply with data regulations.

Data Support and Accessibility

Data velocity is only increasing, and data diversity along with it. Semi-structured data—like JSON—is now the norm. And analytics tools aren’t keeping up: many can only deal with this data once it is flattened. The result? Most people get cut out of the data conversation because they have to wait for data teams to clean and curate it. Be sure to consider whether the tool you choose can support your data types, and doesn’t limit data access for those who need it.

Reporting and Dashboards

With any cloud analytics tool, the ability to generate and share reports and dashboards are a must. Just make sure that’s not where analysis stops. Too many tools rely on visualization and reports, and don’t allow users to ask more questions through exploring data further and drilling down into the trends. Also keep in mind that you want a tool that can keep these reports and dashboards up to date in real time and have embedding capabilities that allow you to share the insights outside of the tool itself, say in an app or on a website. This gets more people involved in the data conversation and helps drive data adoption.

Scalability

When choosing a cloud analytics tool, it’s paramount that you select one that is capable of scaling with your company as it grows. Data velocity will only increase down the road, so plan ahead with the right tool. Whether supporting additional users, reporting, data types, or data sources, scale is something often overlooked. Your analytics tool should be able to not only support your growing needs today, but keep your data, users, and reports organized with future demands as your company and BI needs grow.

Sharing and Collaboration

Collaboration tools have undergone a renaissance. Slack and Google Docs changed how people work together, and set expectations for how easy things should be. Now, cloud analytics tools like Sigma have brought this approach to BI. Collaborative BI means being able to work seamlessly and effortlessly with internal and external partners, easily finding and building on the most relevant analysis. Fully-cloud systems and improved AI-driven algorithms enable new collaborative platforms. This approach is shrinking the data access gap and will help you drive greater adoption by getting data in the hands of business experts who can put it to good use.

UPDATES

Announcing Visual Data Modeling

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Security and Governance

These days, it seems like every time you turn around another company announces a data breach. Historically, many of these breaches have come from insecure data practices surrounding extracting data to spreadsheets that are hard for a data team to track and ensure compliance. The most secure place for data is in the cloud data warehouse. Cloud computing can offer better physical security benefits that on premise. Cloud providers have governance oversight to ensure compliance with security standards, as well as dedicated personnel to keep data at scale secure. When handing over the physical control of your data, you are handing it to a company that specializes in keeping that data online and secure.

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Buyer’s Guide: Building a Cloud Analytics Stack

Ready to migrate to a cloud analytics solution? Read our free Buyer’s Guide first.

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