Tamr’s Virtual CDO is a Game-Changer When it Comes to Self-Service Analytics

Summary:

• Self-service analytics enables data democratization by putting the power of data and analytics into the hands of everyone within the organization.
• Self-service analytics has encountered a few pitfalls, including challenges with data access and governance, inflexible tools, and poor data quality.
• Generative AI (GenAI) is changing the game when it comes to self-service analytics by providing users a way to ask questions about the data so they can enrich it and improve its quality.
• Tamr's Virtual Chief Data Officer (vCDO) helps organizations fix bad data and overcome the "right click and ignore" scenario.

The emergence of self-service analytics nearly a decade ago marked a significant shift in the way organizations used their data, enabling all employees, regardless of title or level, to access, analyze, and visualize data without relying on IT or data specialists. Built on the premise of data democratization, self-service analytics enabled businesses worldwide to put the power of data and analytics into the hands of everyone across the organization, increasing agility and fostering a culture of data-driven decision-making. 

Fast-forward ten years and the data landscape looks quite different. From digitization and Internet of Things (IoT) to social media, streaming, and cloud computing, data volume has exploded. And it’s only going to get bigger and more complex each year. 

Data warehouses, once the mainstay of business, are no longer sufficient. And self-service analytics are struggling to keep pace, mired by pitfalls that prevent them from delivering maximum value to the business. 

3 Pitfalls of Self-Service Analytics

When first introduced, self-service analytics promised to transform businesses by democratizing data for everyone. But they’ve run into a few stumbling blocks along the way.

1. Inefficient data access and governance

A key to successful adoption and use of self-service analytics is the ability for end users to easily access trustworthy data. But making data accessible is easier said than done. Data teams condense massive data warehouses into simple views for data consumers. But inevitably, data consumers often need something different than the views they can access. This puts the data team in a tough spot: 

They can spend weeks or months updating data pipelines and adopting schemas

Or…

They can pull together data to get a quick answer 

Neither option is ideal. Updating data pipelines and adopting schemas is time consuming, which means the data team will likely deliver the information too late. But pulling a view of data together quickly isn’t any better as those views will immediately become out of date. 

2. Complex and inflexible tools

While self-service analytics promised to make data accessible for everyone, the reality is that business intelligence (BI) solutions like drag and drop visualization tools are often complex. End users find them difficult to adopt, while data teams find them to be too limited to serve as a one-stop-shop solution. 

To solve this challenge, many users revert to Excel, which introduces its own set of challenges. Not only are Excel spreadsheets static, but they are also difficult to scale. Further, when users manually manipulate data in spreadsheets, it puts data integrity at risk. Which brings us to our next point.

3. Poor data quality

While self-service analytics tools deliver beautiful visualizations of data, they also mask errors hidden deep beneath the surface. Identifying errors in self-service analytics is challenging and many times, users fail to recognize errors until very late in the process. Furthermore, the “solution” users often default to, especially when they spot outliers in their visualization, is “right click and ignore.” The challenge, however, is that this “solution” only occurs at the presentation layer; the underlying data remains inaccurate. 

In addition, because there is no easy way for users to provide feedback, the source data remains flawed, exacerbating the data quality issues. And while some users may email the data team to provide feedback on the quality issues they’ve uncovered, this solution is hardly state-of-the-art. 

So where does that leave us? Simply put, it leaves you with a mess. Data teams are overloaded with one-off requests for ad hoc views. Data consumers are frustrated because they don’t know if the data they are viewing is complete and up-to-date. And fragmented, siloed data proliferates throughout the organization. 

The upside is that we can do better. 

Introducing the Virtual Chief Data Officer (vCDO)

Having your CDO on speed dial is not exactly practical. But what if you could enable your users with a chat interface that would enable them to ask questions about the data, identify issues with data quality, and resolve them in real time. Sounds too good to be true, right? Well, it’s not. 

Tamr’s Virtual Chief Data Officer (vCDO) enables data users, regardless of their role, to ask questions about the data and resolve issues with it in real time. Using an intuitive, ChatGPT-like interface, users can pose questions such as “was this entity involved in a merger” or “are company X and company Y the same?” 

Using the power of Generative AI (GenAI), Tamr’s vCDO changes the game by making it easy for all users to access internal data sets in real time so they can enrich it and make it more complete. They can also append new data to the organization’s central data assets so that everyone across the organization can benefit from the latest data, regardless of how or where they capture it. 

Using the Virtual Chief Data Officer interface, businesses can overcome the challenges related to the successful adoption and use of self-service analytics by giving users an easy way to fix bad data and eliminate duplicates at the source, eliminating the “right click and ignore” dilemma. 

Isn’t it time that you gave your data users clarity and control over their data? Watch our webinar recording to learn more about Tamr’s Virtual CDO. Then, schedule a demo to discover how Tamr’s vCDO can work for your business.