Back to Videos

AQuA is a quality automation accelerator tool by Infocepts to validate data quality at source, staging layers, production warehouses, and report outputs. It enables scaling of the quality processes as volume, velocity, and variety of data grows.

You get home after a bike ride and check out your average speed, peak heart rate, VO2 max on your Garmin. From here you decide whether you had a “good ride”, or how you can improve next time.

Or, you’re looking into your stocks, and a notification pops-up on your smartphone. You open your trading app, read the news article, study a chart, and then make a trade within the same app.

“What’s common between these two acts?”

As a user, while strategizing about your next ride or making a trade, you are intuitively (almost subconsciously) making data-driven decisions while engrossed in your area of interest. The fact that you are consuming and analyzing data fades away in the background while you focus on the task at hand.

“So why isn’t this the case when I have to make business decisions?” It’s a valid question, and a short answer to it is, embedded analytics.

What is embedded analytics?

Simply put, embedded analytics is the seamless integration of analytic content and capabilities within applications (like CRM, ERP) or portals (intranets or extranets).

According to Gartner, “Embedded analytics is a digital workplace capability where data analysis occurs within a user’s natural workflow, without the need to toggle to another application”

The goal of embedded analytics is to help users make better decisions by incorporating relevant data and analytics to solve high-value business problems and work more efficiently as these capabilities are available inside the applications they use every day. This contrasts with traditional business intelligence tools/platforms, which focus on extracting insights from data within the silo of analysis.

How to get started with embedded analytics

“What are the key considerations for embarking on an embedded analytics journey for my organization?”, “How can Infocepts help?” you may ask. Curious you! But don’t worry, you are asking the right questions. Let’s begin with the second question first.

Infocepts is a global leader of end-to-end data & analytics solutions with nearly 20 years of experience enabling customers to derive value from a variety of data-driven capabilities. Working in partnership with you, we offer reusable solutions to your data and analytic needs to deliver predictable outcomes with guaranteed ROI.

Back to the first question on key considerations – blending our experience, expertise, and a lot of thought, we have put together a list of key considerations in case you are considering about creation and sustenance of embedded analytics applications:

1. User experience (UX) and adoption

The end-users should be able to use and adopt the analytics applications, else all the time and resources spent may not lead to anything.

2. Business Value

How to capture and articulate business value to secure “buy-in” from program sponsor(s) and key stakeholders. This involves creating a business case, identifying metrics to track, and measuring performance over a period of time.

3. Ability to customize, integrate and maintain

These factors determine the effectiveness of the application and ultimately determine whether its adoption is sustainable or not.

4. Governed self-service

Users should be self-reliant to use these apps. Moreover, it’s crucial that they have confidence in the quality of the data and the right person should be able to get access to the right information.

5. Operational efficiency and automation

The analytics application should help the users to do things faster, with continuous improvement.

How we created an embedded analytics solution

We helped a well-known luxury retail customer create an embedded analytics solution within their portal, which eventually helped them realize business value.

The customer had a unique business model wherein travel partners would bring in customers to their stores situated in the choicest of travel destinations around the world as a part of their tour itinerary. These travel partners would log in to a portal provided by our customer and make registrations for the tour groups so that the store operations team could plan their visits accordingly and provide a better customer experience for the tour group within the store.

After analytics were seamlessly embedded within the login portal, travel partners were empowered to get access to key information about their sales, targets, and commissions/incentives in a single place. Here’s how it helped both parties:

Travel partners:

    • Better visibility and actionable insights based on past sales performance trends by customer demographics and product categories helped them plan and hence perform better. For example, they understood from data that people coming from Switzerland to France store may not be too keen to buy watches since they may have already bought those in their initial part of the tour itinerary. Such insights helped the travel partners to plan out, in collaboration with our customer, some tailored store visits thus maximizing sales performance.
    • Data-driven insights also empowered travel partner associates to fast-track their effectiveness, which would otherwise typically take years of experience to understand patterns.
    • Since data points were ‘embedded’ within the same portal which the partners were quite used to working with, the familiar interface meant minimal change management and training, and hence almost 100% adoption.

Our customer:

Retail stores saw a 30% uptick in channel sales due to embedded analytics. Moreover, it reduced the workload on the store operations team in managing the channel partners and their information requests. Instead of pulling one-off reports time and again, they were able to focus their time on other activities to better the business.


Want to learn more? Get started today with your embedded analytics journey and help build a better future for your business and users.


Further, Infocepts was featured as the Top 15 Business Analytics Blogs by Feedspot

Recent Blogs

There is a general belief that narrating stories or data storytelling is a specialized skilled job that must be done by data visualizers or data storytellers using sophisticated design and BI tools. However, it is imperative these days that everyone becomes a data storyteller in some capacity. With increasing data volumes and heightened interactions with data daily, having visual communication skills, is a powerful skill to have.

So, how do you do this? Whether it is a client presentation, pitching clients, quarterly business reviews, or internal team discussions, opportunities are endless to become a Data Storyteller. You might even be doing it already and not even know it!

There are five key focus areas to master becoming an effective Data Storyteller.

1. Visual thinking

Usually people often tend to present facts and figures in their absolute form such as charts and tables, without any storyline or narration around it. For the audience, it is difficult to consume or remember trends and patterns in the charts. Here is where Data Storytelling comes into play.

Take your common spreadsheet full of data highlighting your company’s quarterly results. This might be presented to the audience in a formal setting and the purpose is declarative. Instead, if you were to utilize the art of Data Storytelling, you start to think visually, considering the nature and purpose of the visualizations. Before presenting, ask yourself these two questions:

Is the information conceptual or data-driven? Here the goal is to present the idea.
Am I declaring something or exploring something? Here the goal is to inform and enlighten.

2. Which hat do you wear when you see the data?

Narrating a story from the data can often be complex and time consuming if not done right. Beginning with data in its raw stage to the final output of presentation; a data set gets processed and passed upon through multiple profiles. When working with data sets there are four hats from a domain expert to an analyst, to a statistician, and finally a designer that you should wear.

3. Sketch an idea from the data

You don’t need to be a graphic design expert, using something as basic as pen and paper you can easily sketch out what you want to get across as a first step. Sketching out the data can help integrate various kinds of knowledge at the ideation stage. De-cluttering a heavy data set by sketching helps to identify relevant information, its hierarchy, and flow.

Sketching relies on conceptual metaphors, taking place in more-informal settings, such as off-sites, strategy sessions, or early-phase innovation projects. It can be used to find new ways of seeing how the business works or to answer complex managerial challenge such as restructuring an organization, producing a new business process, or codifying a system for decision making.

4. Power of metaphors in data storytelling

Have you ever visualized an area chart that resembles a mountain? As a metaphor, mountain can be used as an element of expression on how the company sales performance grew over the years touching its peak.

Numerous metaphors are woven into the fabric of data science itself, such as data warehouses, data lakes, and data mining. When narrating stories, metaphors are essential for breaking down language barriers that stand between you and your audience. They work best when you have complex concepts or ideas to convey. Advantages of using metaphors are they:

  1. Make the story more interesting and fun
  2. Keep the audience engaged
  3. Help bring the meaning and significance of the data to the forefront
  4. Assimilate the unfamiliar by comparing it to what is familiar

5. Getting personal with data story telling

More often than not, more time is spent gathering the data than actually composing the story around it. Without a good data story, visualizations are relatively ineffective. The story connects the dots between the data and the audience. It reveals the data’s meaning and significance, educates, and transforms the audience.

Based on Freytag’s pyramid theory, every story has a beginning, a middle, and an end. Each of them has a different purpose. When structuring your story, be sure that each part achieves its purpose.

Moral of the data story

The data story you tell an audience requires more than just data and visualizations. Good data is only one essential element. A good data story is one that engages, entertains, educates, and transforms the audience to act upon it.

Ready to get started? No matter where you are in your data storytelling journey, we are here to help. Get started now!

Recent Blogs

BI Converter is an accelerator that automates migration from a specific source to a target BI platform helping organizations modernize their BI stack without vendor lock-in. It accelerates any migration saving time and costs, reducing dependency on niche skills.

The COVID-19 global pandemic disrupted many established business models, forcing companies to embrace digital transformation to remain relevant. The use of data & analytics is altering the competitive dynamics in all industries. According to Forrester Research investments in D&A capabilities are paying off. Firms with advanced data & analytics capabilities are 2.8x more likely to report double-digit year-over-year growth. But while companies are investing in cloud, data, and automation technologies, business results from these investments are not yet paying off.

Getting business results from D&A investments requires leaders to define digital models, create new ways of working, find human expertise, and balance speed and agility. Successful companies must excel in all five key D&A competencies: strategy, people, process, data, and technology. Companies that underinvest or deprioritize efforts associated with any one of the required competencies fail to achieve results promised by their D&A strategy.

Watch Infocepts’ CEO, Shashank Garg, and guest speaker, Boris Evelson, VP and Principal Analyst, of Forrester Research as they share their top recommendations for D&A leaders to avoid pitfalls and accelerate their success including:

• Top challenges with getting results from D&A strategies
• Shifting mindsets when planning for D&A strategy and execution
• Strategies to accelerate results from D&A investments
• Recommendations for making progress within your organization

Accelerate results from your data and analytics investments. Watch now.