Business Analyst training without embedded analytics is a blunt proposition. If you want to succeed in the competitive world of Business Intelligence, take to Embedded Analytics with gusto.
Not long ago, data was considered as the most prized possession of a company, It helped the data organization design, run, and analyze various key facets of the business using BI and BA tools. It actually helped them stay relevant to the market and outpace their competitors. But, then came Embedded analytics and the supreme power of AI and Machine Learning that changed the whole paradigm associated with data management and analytics!
In this article, I have shared the top ways any business analyst can take to embedded analytics in their business analyst training course.
Working with the Data Mashup
The value of working with data mashup is simply unmatched.
Business analysts are a force to reckon with when it comes to integrating reports and applications into a single platform. Embedded Analytics training during the BA / BI course helps analysts to understand and better access the business information from more than one source. The biggest advantage of working with Embedded Analytics is its ability to comply with data mashup standards — that is, bringing the ability to embed not just data, but also reports, dashboards, and applications at your fingertip. Working with more than one set of data not only improves the final outcome but also prepares the BI teams to make more progressive decisions.
Turning Analytics into Center of Excellence (CoE)
The best embedded analytics platform allows teams to focus on building not just the product and best practices, but it also helps in saving time, optimize resources, and reduce the cost of operations, thereby maximizing the profit.
I have, for years, now proposed that organizations must look at Analytics, as a COE tool, which can help make the best sense of all the reports and data that are fed into the most used and most analyzed business apps. Embedding analytics at CoE targets best practices that need to be complied with., enabling users to access analytics tools that will improve its adoption across organizational levels.
Embedded Analytics for Customer Experience
We are living in an era where customer experience is everything- and how could embedded analytics be far from CX goals. Embedded analytics, when applied with traditional BI tools, enable users to share their team’s performance with a larger audience group, who then contribute their own analytics to build customized audience segments, also called intent-based cohorts. This is exactly what Google and Facebook’s data science team do– they segment audiences based on intent, behavior, and profiles.
This embedded analytics technique specifically focuses on how marketing and sales teams could communicate with their customers, without requiring any additional information within the BI system. It auto-feeds through CRM, Social media, and Email contact lists, in addition to also improving targeting and advertising efforts.
Indigenous Applications that Suit Your Organization Goals
Also called “Home-grown” business applications, these apps help solve complex challenges that the company has to face on a daily basis. Without fearing data leaks and privacy breaches, these apps use embedded analytics to augment services to users, mostly company managers and staff officers.
Every department in the company now has its own set of apps for analytics and communication boards. The marketing team has its own CRM, marketing intelligence, and communications apps. The sales team has their forecasting and revenue automation tools; Finance has their invoice tracking and CPQ tools, IT has their AutoML and cloud computing analytics, and so do HR who have analytical and employee engagement dashboards. So, analytics is a home-grown proposition for many high flying organizations who want to ingest as much data from outside as from inside their own departments. So, companies are investing in building their own apps.
Many businesses have development teams that create home-grown or customized solutions to solve the company’s business problems. These developers are generally successful in creating a solution that works but lacks additional features such as analytics. This is where embedded analytics shine because it wouldn’t necessarily make sense for internal developers to also develop a full reporting function with scheduled reporting and notifications to the custom solution if it’s not core to the problem.
Today, data is just a raw material that anyone could possess – what has become the key differentiator is the way business analysts use embedded AI and Analytics to make smarter, agile decisions for a better future.