Driving self-service analytics on the modern data stack

Fintech companies AJ Bell, OrderPay and Tide are blazing a path to better insights with a modern approach to data: self-service analytics.
January 10, 2023

Experience is the best teacher, they say – and for good reason. As businesses navigate the current economic environment and societal change, learning from the experience of others is a priceless — and costless — opportunity. We were delighted to see so many data leaders share this sentiment and turn out in such great numbers at the latest Fivetran After Five event, which took place recently at The Brewery in London. 

The topic of the session was how to drive self-service analytics across an entire organization so that different teams and departments can quickly and easily access the insights they need.

Joining us on stage were two of our strategic partners: ThoughtSpot, a search and AI-driven analytics provider and Snowflake, the leading Data Cloud provider. Together, Fivetran, Snowflake and ThoughtSpot help enterprises automate their data stacks so they can fulfill their ambitions to support self-service analytics.

We were also excited to hear from three of our joint customer organizations, all of which have automated their data processes in order to make data more accessible and to bolster their business decision-making capabilities.

During the course of the evening, we heard from AJ Bell, the award-winning investment platform, OrderPay, which facilitates faster, cheaper payments for the hospitality and leisure industries and Tide, which provides mobile-first bank accounts and financial administration services to 450,000 small businesses.  

Here are our three takeaways from this lively discussion.

Access to data is a top priority, and it’s getting more important

Lines of business and senior leaders are crying out for data that is timely, complete and accurate. Whether it’s to report on operational processes, marketing programs, financials, risk exposure or any other business metric, we heard about the growing requirement to place information at the fingertips of the people who need it. These people don’t want to wait days or even weeks for data analysts to pull reports; they need the information in minutes, and they need it to be accurate and comprehensive.

It’s not just reporting that’s important to these businesses. All of the customer panel participants shared their experiences of rolling out predictive and/or advanced analytics to underpin even better decision-making in the future. All expect advanced analytics to be a major focus in coming years.

The conversation wasn’t limited only to technology. There was much debate about the desire to create a culture of data within their organizations, where information is readily available to everyone, without any heavy-lifting from data scientists or engineers, who are often called on to build connectors that integrate data from various silos across the organization.

It’s clear that facilitating self-service data analytics requires a cultural shift as well as a technological one.

Legacy technology creates a myriad of challenges

This desire to place data at the very center of corporate culture is in stark contrast to the panelists’ stories about their experiences prior to their modern data stack implementations. While the three organizations had very different legacy tech solutions in place, they all raised common challenges.

Growing datasets and an increasing number of corporate and cloud applications made it difficult for often small data teams to keep on top of requests to create dashboards, build reports and derive insights. It wasn’t just the data teams that were feeling the pressure; it was impacting engineers, too, as they were responsible for building more and more manual data pipelines. In short, data scientists and engineers – both of whom are highly skilled – were sometimes bogged down by manual, routine processes that prevented them from focusing on more strategic business priorities. This is a common issue for organizations across the board and, as recent research reveals, one of the biggest inhibitors of AI maturity.  

Reliability was another often-repeated issue. We heard how data teams regularly gave up time on their weekends to mend broken data pipelines, of business leaders’ frustration about the unavailability of reports, and how some datasets weren’t leveraged at all.

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Automation is reaping rewards

AJ Bell, OrderPay and Tide are very different businesses, so it’s perhaps unsurprising that they are leveraging different solutions to tackle these challenges and optimize their data stacks. However, in all three cases, automation is reaping rewards.

We learned how AJ Bell can now pinpoint the times of the week where customers are most and least likely to convert, and take appropriate action to boost order completions. On a more personal level, its data team told us they now have their weekends back – for the first time in five years.

We found out that OrderPay’s analysts no longer need to rely on engineers’ time and resources to be able to access key data, while its partners and internal teams have been empowered to create their own dashboards and reports. By automating and streamlining these processes, its team has freed up 20 percent of its time to focus on more strategic initiatives.

We also heard how Tide has successfully democratized access to data across its entire (fast-growing) organization, while at the same ensuring that strict governance controls are in place to protect sensitive customer information.

Ready to drive your self service analytics?

If you’re interested in hearing more about how Fivetran and its strategic partners are helping companies such as AJ Bell, OrderPay and Tide automate their data processes, sign up today for a demo

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Join the thousands of companies using Fivetran to centralize and transform their data.

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Blog
Blog

Driving self-service analytics on the modern data stack

Driving self-service analytics on the modern data stack

January 10, 2023
January 10, 2023
Driving self-service analytics on the modern data stack
Fintech companies AJ Bell, OrderPay and Tide are blazing a path to better insights with a modern approach to data: self-service analytics.

Experience is the best teacher, they say – and for good reason. As businesses navigate the current economic environment and societal change, learning from the experience of others is a priceless — and costless — opportunity. We were delighted to see so many data leaders share this sentiment and turn out in such great numbers at the latest Fivetran After Five event, which took place recently at The Brewery in London. 

The topic of the session was how to drive self-service analytics across an entire organization so that different teams and departments can quickly and easily access the insights they need.

Joining us on stage were two of our strategic partners: ThoughtSpot, a search and AI-driven analytics provider and Snowflake, the leading Data Cloud provider. Together, Fivetran, Snowflake and ThoughtSpot help enterprises automate their data stacks so they can fulfill their ambitions to support self-service analytics.

We were also excited to hear from three of our joint customer organizations, all of which have automated their data processes in order to make data more accessible and to bolster their business decision-making capabilities.

During the course of the evening, we heard from AJ Bell, the award-winning investment platform, OrderPay, which facilitates faster, cheaper payments for the hospitality and leisure industries and Tide, which provides mobile-first bank accounts and financial administration services to 450,000 small businesses.  

Here are our three takeaways from this lively discussion.

Access to data is a top priority, and it’s getting more important

Lines of business and senior leaders are crying out for data that is timely, complete and accurate. Whether it’s to report on operational processes, marketing programs, financials, risk exposure or any other business metric, we heard about the growing requirement to place information at the fingertips of the people who need it. These people don’t want to wait days or even weeks for data analysts to pull reports; they need the information in minutes, and they need it to be accurate and comprehensive.

It’s not just reporting that’s important to these businesses. All of the customer panel participants shared their experiences of rolling out predictive and/or advanced analytics to underpin even better decision-making in the future. All expect advanced analytics to be a major focus in coming years.

The conversation wasn’t limited only to technology. There was much debate about the desire to create a culture of data within their organizations, where information is readily available to everyone, without any heavy-lifting from data scientists or engineers, who are often called on to build connectors that integrate data from various silos across the organization.

It’s clear that facilitating self-service data analytics requires a cultural shift as well as a technological one.

Legacy technology creates a myriad of challenges

This desire to place data at the very center of corporate culture is in stark contrast to the panelists’ stories about their experiences prior to their modern data stack implementations. While the three organizations had very different legacy tech solutions in place, they all raised common challenges.

Growing datasets and an increasing number of corporate and cloud applications made it difficult for often small data teams to keep on top of requests to create dashboards, build reports and derive insights. It wasn’t just the data teams that were feeling the pressure; it was impacting engineers, too, as they were responsible for building more and more manual data pipelines. In short, data scientists and engineers – both of whom are highly skilled – were sometimes bogged down by manual, routine processes that prevented them from focusing on more strategic business priorities. This is a common issue for organizations across the board and, as recent research reveals, one of the biggest inhibitors of AI maturity.  

Reliability was another often-repeated issue. We heard how data teams regularly gave up time on their weekends to mend broken data pipelines, of business leaders’ frustration about the unavailability of reports, and how some datasets weren’t leveraged at all.

[CTA_MODULE]

Automation is reaping rewards

AJ Bell, OrderPay and Tide are very different businesses, so it’s perhaps unsurprising that they are leveraging different solutions to tackle these challenges and optimize their data stacks. However, in all three cases, automation is reaping rewards.

We learned how AJ Bell can now pinpoint the times of the week where customers are most and least likely to convert, and take appropriate action to boost order completions. On a more personal level, its data team told us they now have their weekends back – for the first time in five years.

We found out that OrderPay’s analysts no longer need to rely on engineers’ time and resources to be able to access key data, while its partners and internal teams have been empowered to create their own dashboards and reports. By automating and streamlining these processes, its team has freed up 20 percent of its time to focus on more strategic initiatives.

We also heard how Tide has successfully democratized access to data across its entire (fast-growing) organization, while at the same ensuring that strict governance controls are in place to protect sensitive customer information.

Ready to drive your self service analytics?

If you’re interested in hearing more about how Fivetran and its strategic partners are helping companies such as AJ Bell, OrderPay and Tide automate their data processes, sign up today for a demo

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