LinkedIn

Twitter

GitHub

dashboard-4-300-1-image-unique-image-unique

dashboard-4-300 1

<div class="note-with-imagestyles__Text-sc-1lyjb6c-5 jayydY">
<div class="sanitized-html__StyledDiv-sc-1x0zpzc-0 hjBqVG">
Build visual, interactive experiences using sample data to experience the power of infusing analytics on our cloud.
</div>
</div>

Try Sisense for free

Whitepaper

Technology advancement is fundamentally an act of democratization–once-specialized capabilities become cheaper, simpler, and more accessible to all, fostering broad adoption and the development of creative new applications and solutions to long-standing problems. 
The same should be true of data and analytics &#8211; but so far, it hasn’t been. The promise of BI was to put the power of data into the hands of everyday people so that everyone could make smarter, data-driven decisions. We know, however, that we have yet to really see this promise come true. Although self-service analytics put reporting tools in the hands of business users, we still largely rely on specialists to interpret and contextualize our charts and dashboards–and for many of us, to build them. Since business intelligence tools are generally bought by specialists who expect advanced capabilities and have complex use cases, those tools have a steep learning curve which leaves most knowledge workers behind.  We have yet to truly democratize data analytics and seamlessly deliver insights from data into the hands of everyone.
While analytics takes a specialized skillset, advances in natural language querying, machine learning and data transformation have made it practical to deliver insights directly to workers in the context of their decisions. Coupled with a flexible analytics platform and developer-friendly integration points, it is now possible to skip the fruitless BI training and equip users with data in the applications they already use.  Now we are beginning to see incredible examples of what people are capable of when they actually have the power of data in their own hands.
<h2>Democratized data in action</h2>
Imagine an airline where every employee uses insights from data to make decisions throughout the day. Front-line employees, such as gate agents, receive relevant KPI alerts no matter their physical location. Executives discuss and iterate on different policies in real-time using live, interactive data. Safety managers predict which airplane parts are at risk of failure and proactively bring the planes in for inspection. Don’t believe it? This airline actually exists today. It’s <a href="https://www.sisense.com/press-release/air-canada-implementation/">Air Canada</a>.
<img decoding="async" loading="lazy" class="alignnone wp-image-734678 size-large" src="https://cdn.sisense.com/wp-content/uploads/Air-Canada-Graphic-inline-1200x300-1-1024x256.jpg" alt="" width="1024" height="256" srcset="https://cdn.sisense.com/wp-content/uploads/Air-Canada-Graphic-inline-1200x300-1-1024x256.jpg 1024w, https://cdn.sisense.com/wp-content/uploads/Air-Canada-Graphic-inline-1200x300-1-300x75.jpg 300w, https://cdn.sisense.com/wp-content/uploads/Air-Canada-Graphic-inline-1200x300-1.jpg 1200w" sizes="(max-width: 1024px) 100vw, 1024px" />
Rather than continuing to centralize insights from data in dashboards, analytics tools, and other data specialists, Air Canada took the opposite approach: They used AI to extract those insights and infuse analytics into many different facets of their business’ operations. Importantly, they took advantage of the devices their employees were already using, such as mobile devices, smartwatches, and even smart speakers. Employees no longer needed to pause their work to find a computer, sign in to a portal, and wade through dashboards, emails, and PDFs in search of data. Instead, the company pushed the relevant insights to them, personalizing the data and the delivery method based on the employee’s role and where they work.
This is democratized data analytics in action. Everyone in the company making smarter decisions throughout the day without ever leaving their existing workflows or having to learn entire new skill sets. For Air Canada, this has improved both their bottom line, but has also improved safety for its employees, its customers, and all airline travelers.
Air Canada’s solution hinges on two essential elements. First, an analytics platform capable of refining raw data into actionable insights. Second, developer APIs required to feed context from their applications into the analytics stack, and processed insights from the data side back into their native applications.  With Sisense, Air Canada has gone far beyond traditional BI tooling, and further than what most embedded analytics products can deliver.
<h2>Business analytics is stuck</h2>
If democratizing data analytics provides so many benefits to companies like Air Canada, why don’t other companies follow suit?
The answer is that it requires a fundamental evolution in how we approach analytics in the first place. Most companies today ask their knowledge workers to make data-driven decisions by first learning additional tools. These tools come in the form of standalone dashboards and self-service analytics apps, which despite improving on the days of submitting data requests to IT, still require training, upskilling, and sometimes even enrolling in certification courses. This takes too much time that knowledge workers don’t have, and it often doesn’t even work.
If we truly want to democratize data analytics, we have to enable knowledge workers to make data-driven decisions without learning an entire new discipline. Like Air Canada, we need to extract the insights from data and infuse them into workers’ existing workflows, apps, and devices. Imagine a CRM that crunches data to automatically suggest which accounts to contact, a customer service platform that proactively identifies accounts likely to churn, or a retail app that detects shifts in purchasing trends and recommends changes in inventory.  Or an integration into Google Sheets and Microsoft Excel that lets a user find data in their Snowflake database using natural language querying, and imports it as an always-up-to-date spreadsheet.
All of these examples empower knowledge workers to make smarter decisions without them pausing to dig through separate dashboards for insights. In short, we bring the insights from data directly to people, and not the other way around.
<h2>Creating new opportunities with analytics</h2>
It’s understandable that many people wonder if data and analytics will turn us into optimization robots that act however the data tells us to act, but the truth is precisely the opposite. Like other technologies, when we put analytics and insights from data into the hands of everyone, we all benefit. In fact, we’re beginning to see people use analytics in creative new ways and even invent entire new products and services.
Take Personica, for example, a restaurant marketing platform that has helped restaurants adapt and become digital businesses overnight in the midst of a global pandemic. For example, pizza restaurants (a business profile that rarely sports a BI professional) can now develop a ‘best guest’ profile, tweak it with real-world performance testing, leverage loyalty programs to measure segmentation and penetration, and tune demand marketing in response.
Or Freckle, an education company empowering schools to understand student progress using data. Having found that dashboards weren’t getting through to school administrators, Freckle shifted to embedding insights on student progress &#8211; not just aggregate data &#8211; directly into the product, allowing school administrators to have real-time analytics on their own, in the app they were already using, without learning additional technical skills to navigate self-service dashboards. With data at their fingertips, administrators are now able to work with teachers to identify how everyone uses the product, which exercises are most beneficial, and which students might need further attention.
This is what’s possible when we democratize data analytics. These examples aren’t possible because of specialist reporting teams in IT or self-service BI tools delivered to business users.. They are possible because everyday people simply have the insights from data to make smart decisions.
<h2>How to get started with Infused Analytics</h2>
If you’re already using Sisense Fusion for your analytics, and you use <a href="https://sisense.com/marketplace/infusion-slack/">Slack</a>, <a href="https://sisense.com/marketplace/sisense-analytics-for-google-slides/">Google Apps for Business</a>, MS Teams or <a href="https://sisense.com/marketplace/sisense-analytics-for-salesforce/">Salesforce</a>, download and install the Infusion Apps today and take the first step towards democratizing data.  Or learn more about what each app can do by exploring <a href="https://documentation.sisense.com/docs/infused-analytics">the documentation</a>.
If you haven’t adopted Sisense Fusion yet, <a href="https://www.sisense.com/get/demo/">watch a demo</a> to learn all the capabilities of a modern analytics platform.
<h2>What comes next in business intelligence</h2>
Sisense is leading the way in democratizing data using its AI-throughout analytics platform, Extense framework for integrating data directly into native applications, and pre-built Infused Apps for many common business productivity tools, already in use by thousands of knowledge workers underserved by traditional BI.
This is the future of analytics, and the most innovative companies will help usher it in now. They will put insights from data in the hands of everyone, where they already are, and in doing so, everyone will benefit, perhaps in ways none of us could have previously imagined.

4 of the Most Innovative Ways Companies are Using AI to Transform Data Democratization

Try Sisense for free