DATA ANALYTICS

The Definitive Guide to Embedded Analytics, Dashboards & Reports

Devon Tackels

Content Marketing Manager, Sigma

More and more, companies that seek to be data-driven are discovering that it takes a village. The limited perspectives of the few people on the BI team just aren’t enough to identify all the available relevant data, use it effectively, and produce real-time insights for decisions at every level. Organizations of all types are now realizing the value of community-driven collaboration. Ventana Research found that nearly four in 10 companies are using collaboration to support data analytics, while more than half said they expect to use these capabilities in the future.

To benefit from community-driven analytics, however, you must have tools that bring together a variety of perspectives and allow people from a spectrum of backgrounds to fully participate. Embedded analytics is foundational to data collaboration. In this guide, we look at exactly what embedded analytics is, the benefits you can expect to enjoy from embedded analytics, essentials for success, use cases, and what to look for in an embedded analytics platform.

What is embedded analytics?

Embedded analytics tames cumbersome workflows and increases the speed and ease of data discovery by adding dashboards and visualizations directly into internal and external applications. Embedded analytics allows you to authenticate users through those apps while maintaining data permissions directly from the analytics tool. With the most modern tools, you can further extend these analyses to partners and customers for a truly community-driven approach.

Get more answers by reading Embedded Analytics 101

How embedded analytics is different from traditional BI

Embedded analytics is quite different from traditional BI in four primary ways, each of which has a big impact on your organization’s ability to be data-driven.

Who can participate — With traditional BI, only those with technical expertise and SQL skills can participate in modeling, querying, and creating visualizations. Business users must rely on the BI team, which creates bottlenecks. With embedded analytics, on the other hand, users of all types can participate, including line of business teams, partners, vendors, and even customers.

Reporting and analytics from a variety of perspectives — Traditional BI typically looks at the data from a limited number of viewpoints (those of the data or BI team). With embedded analytics, those generating the data and who are closest to the meaning of the data can share their knowledge and perspectives — enabling them to work with the data to find answers on their own.

Types of decisions supported — Because traditional BI relies on data and BI teams, who only have so much time available to devote to reporting, management-level decisions are typically the only ones being supported by data. Embedded analytics brings more resources to bear, meaning data can inform a broader range of decisions.

Accessibility — Traditional BI requires that real-time reports and visualizations be viewed within the analytics tool, which is most often unfriendly to business users. Embedded analytics makes reports and visualizations available within existing workflows, software, and systems —allowing non-technical users to easily work with and benefit from data insights.

Why an embedded analytics platform is foundational to a collaborative approach

Success and your company’s ability to stay competitive depends on your team moving quickly in a way that simultaneously ensures compliance. Collaboration is compromised when you’re limited by static tools with limited functionality. Embedded analytics solves two significant challenges to a collaborative state of flow: slow time to insights and sloppy governance.

With the right embedded analytics, users can ask follow-up questions of the data for themselves, and they aren’t required to toggle back and forth between two separate systems. They can quickly and easily contribute their knowledge and perspectives to get the answers they need using tools that are familiar. Additionally, embedding ensures that users are more likely to see and act upon analytic insights. When reports and visualizations are easily accessible and at the forefront of their workflows, users of all kinds will participate and take advantage of them — delivering greater ROI on your data investment.

Embedded analytics also helps with compliance. Collaboration without an analytics tool that’s designed to be community-driven will result in governance nightmares. When permissions remain intact and users work within the parameters of the analytics tool’s security features, data governance becomes much easier.

Benefits you’ll experience with embedded analytics

Embedded analytics applications come with a bounty of benefits. Let’s explore five of the most significant.

Flexible data sharing

Embedded analytics gives you complete flexibility in how you share insights. You can keep reports and visualizations in-house, or you can share them more widely. The specifics will vary by platform, but in Sigma, flexible embedding works by generating and embedding a unique and secure URL of the dashboard or dashboard visualization you want to share, then by placing that generated URL into an iframe in your application. This secure URL contains fields to define what your viewers will see, fields to ensure that the URL is unique, and a signature that’s created by encrypting the URL. In other words, a completely-secure solution to showing exactly what you want to share with exactly the people you want to share with.

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 Encourage data-driven decision-making

Thanks to the fact that users of all types can be involved in embedded analytics, business users in marketing, sales, finance, or operations can generate real-time insights quickly. This means more insights covering a wider range of questions. As a result of this abundance, data-driven insights can inform all types of decision-making — strategic, tactical, and operational. There’s no longer a limit on what types of decisions get data or BI team resources allocated to them.

 Increase productivity

When line of business teams can run their own analyses, they don’t need to wait around for the BI team to deliver dashboards or reports. They can handle their own information needs, making them much more efficient. At the same time, data and BI teams become more productive too because they no longer have to spend the majority of their time running reports — they can, instead, focus on work more aligned with their specialized skills. As you implement embedded analytics, you’ll see a rise in productivity and insight-driven decision-making in the organization.

 High adoption boosts the ROI of your analytics investment

The combination of more decisions informed by data — and greater productivity — translates to a better return on your analytics investment. As people experience the benefits of using insights in their day-to-day work, they’ll put the tool to even greater use. According to a survey by Dresner Advisory Services, embedded analytics tools have an average 59% adoption rate compared to the 27% average adoption rate of traditional BI tools. Additionally, you can generate even more ROI by turning your data into a product — next up.

59%

The adoption rate of embedded analytics tools.

 Transform your data into a product

Many organizations are generating unique, valuable data that customers and partners would happily pay to access. Embedded analytics makes it easy to transform your data, reports, and visualizations into a product that generates revenue or can be used as a value-add for existing products or services — allowing you to be more competitive, or even raise pricing.

Essentials for success in embedded analytics

While an easy-to-use, high-functionality tool is essential for implementing embedded analytics, purchase won’t guarantee success. Be sure you cover each of these must-have features as well.

Provide a strong user experience — There are two important aspects to UX. First, the tool you choose should offer a seamless user experience. Can embedded dashboards be customized according to each user’s needs? Ideally, each user’s dashboard will contain the functionality that user needs, no more and no less. Additionally, depending on the use case, you may want to consider customizable branding. Another thing to think about is the user experience of the implementation. How easy is the embed process? A simple process will preserve your resources, speed implementation, and increase adoption. And you can get to value delivery quicker.

Identify the functionality each user type will need — Another important set of details that will influence your choice of a tool is the functionality each user type will need. What types of data do they need to be able to work with? What specifically will they need to be able to do with the data? (Modeling? Querying? Creating visualizations?) Match the capability needs with the functionality required in your embedded analytics platform.

Consider where and how analytics will be embedded — Where do you want to embed analytics, and how integrated do you need the analytics to be? Embedded analytics may be “bolted-on,” providing security but little else in the way of integration, or may provide a seamless user experience with full integration (and a variety of in-betweens). The most robust type of integration offers data discovery and complete, real-time analytics functionality within the external platform interface.

Quantify the value of analytics for each user type — You’ll dramatically improve user adoption if they understand exactly how the tool will help them reach their goals, save them time, and improve their work. Identify the value that participating in analytics will bring to each user type. In order to help users understand the value and get the most from your embedded analytics BI tool, you’ll also want to invest in analytics training and data literacy. This training isn’t designed to turn non-technical users into technical ones, but to prepare them to participate in the data conversation, discover meaningful insights, and drive business growth.

Embedded analytics examples

There are four key use cases that companies are finding especially valuable today.

Public web pages

When you want to make the public aware of data that’s continually changing, creating an embedded analytics visualization is the ideal solution. Using a simple HTML embed code, you can share visualizations, dashboards, and reports that automatically update as data changes. A timely example is COVID-19 pandemic data. Up-to-date infection rates, death counts, test-positive percentages, and more are now available on a variety of news sites and public health sites for the public to stay informed.

 PRO TIP

Check out Building a Data Literacy Program from the Ground Up to learn more about how to create a training program.

Internal web portals

Insights intended only for your team can be embedded into internal web portals. The advantage of web portal pages is that several data reports and visualizations can be grouped together for ease of interpretation or for diving in deeper while looking at context. These pages can also be used to feature important dashboards that you want your people to be able to easily find and use.

Third-party applications

Embedding analytics capabilities directly into third-party applications allows teams to streamline existing workflows without having to exit the software they find familiar. People can query and visualize data directly in the software they use every day. This capability is especially beneficial for sales and marketing teams. Being able to produce relevant analyses within Salesforce and other applications leads to faster and more informed decision making by eliminating the need to switch between applications to access the data that users need.

Application embedding- a Sigma dashboard embedded into Salesforce

Customer products

We mentioned creating data products when we discussed benefits, but data products are another valuable use case. In a recent webinar, Chris Lambert, CTO of Payload, explains the benefit of making data available to customers: “With Sigma’s application embedding capability, we were able to create data-rich and interactive dashboards that show our customers all of the key metrics they need for daily decision-making and embed them directly into our proprietary products without any interruption to the service we provide to our customers.”

The potential uses for embedded analytics is far reaching. When you implement embedded analytics, you open up myriad new opportunities for your organization, your team members, your partners, and your customers.

Must-have features to look for in embedded analytics applications

Different embedded analytics platforms have different capabilities. In order to experience the benefits that come from community-driven analytics, you’ll want to find one with the following features.

Dashboards

Customizable dashboards — Processes will be more efficient if users can create custom dashboards and/or leverage pre-built themes and layouts. You’ll want the ability to embed images, videos, and URLs into dashboards.

The ability for technical and non-technical users to explore data — Technical users should have the ability to work with SQL, or they’ll be unnecessarily limited. At the same time, non-technical business users should be able to work in an interface that’s simple and familiar, like a spreadsheet. Everyone should have access to dynamic filters and parameters within the dashboard to drill down into the data beneath surface-level reports and run “what if” analyses.

Team workspaces where relevant data is made readily available — People shouldn’t need to go hunting for data that’s relevant to their questions. For example, the marketing team should have its own workspace where all of the data relevant to marketing is clearly labeled and accessible. This encourages people to turn to trusted data often when they have questions.

Automatically refreshing dashboards — You’ll want to be able to view real-time data in your dashboards, so they should automatically refresh. Dashboards should be accurate at any given moment, as the underlying data and analyses change. Otherwise, teams can act on information that’s out of date.

SIGMA IN ACTION

Sigma customer Payload creates data-rich embedded dashboards for its customers.

Sharing

The ability to reuse and repurpose dashboards — People should be able to share their work and build upon one another’s work securely, using role-based permissions.

Flexible embedding — You should be able to embed dashboards and visualizations in context, wherever they’re most relevant.

Application embedding — To fully benefit from what embedded analytics has to offer, you should be able to embed dashboards and visualizations across third-party applications. And application users should not need to create separate accounts in your analytics tool.

Security — It goes without saying that the tools should use role-based permissions for easy governance and utilize functionality like signed embedding to ensure data only goes where it should go and viewers only see what they are meant to see.

Embedded Analytics is the Key to the Benefits of Collaboration

Without a good embedded analytics tool, collaboration is certainly possible, but it’s limited. You need embedded analytics to ensure adoption, benefitting from the knowledge and perspectives of people in a variety of roles, and to generate insights to inform a wide range of decisions in a timely manner. Additionally, the ability to share dashboards and visualizations and build upon one another’s work is foundational to collaboration. All of these capabilities are found in embedded analytics.

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