- AZK Media
Experts reveal what it takes to build a great modern data stack
In this article, Ignatius Bourke, Alliances Manager, Technology Partners from Fivetran, and Rohan Persaud, Director of Channels and Alliances APAC from Sisense, explore what it takes to build a great data stack to improve efficiency and retain competitive advantage.
While the business world remains deep in the throes of sweeping uncertainty amidst the pandemic and volatile economic events, one thing remains certain: organisations need to be data-driven to survive.
It’s time to take a new approach. Businesses can’t rely on what used to work. Instead, they must focus on what will work. And to that, data is the answer. But not just any data, organisations need to take advantage of the right data at the right time to make swift decisions for their own good.
“When you look at the new business norm today, it’s all about the shift from descriptive analytics or the, ‘What happened in the past?’ to predictive analytics, ‘What’s going to happen?’ to even more, prescriptive analytics, which says, ‘What do I need to do?’” asks Rohan Pursaud, Director of Channels and Alliances APAC at Sisense.
“At the end of the day, a data strategy looks at new business models in the right context thanks to insights.”
According to Gartner, however, many organisations are struggling to get business value from their analytics. Through 2022, only 20% of analytic insights will deliver business outcomes. And when it comes to artificial intelligence (AI), Gartner predicts that 80% of projects will remain “alchemy, run by wizards whose talents will not scale in the organisation” this year.
Implementing analytics projects or an analytics organisation is one thing, but extracting value from it is quite another. That’s where a modern data stack (MDS) comes in. Simply put, an MDS is a suite of tools used for data integration. And it’s a boon for businesses of all sizes.
What does the modern data stack (MDS) look like?
The function of a modern data stack is to facilitate the ingestion of data from multiple sources into a centralised location where it can then be analysed.
It’s made of four basic components:
data ingestion solution
data warehouse or data lake
transformation tool; and
business intelligence (BI) tool
But assembling this MDS doesn’t have to be complex. It’s all about choosing combinations that are the best fit for your business. After all, the ultimate goal of an MDS hinges on using data to create the best customer experience possible.
An MDS is more than the sum of its parts or its specific tools; what makes a stack modern is its ability to meet the different demands caused by modern data problems at each phase of the data lifecycle – what happens to data from when it is created to when it is ready to be actioned as an insight.
“That’s how data strategy is tied to growth – it’s about tackling new complex questions, questions we never anticipated,” adds Rohan.
Taking the first step on the data ladder
The first step in building a data stack is identifying exactly what it is that you’re trying to calculate and measure. This will help guide you towards the type of data you need to source.
For example, Australia’s largest pet ecommerce store Pet Circle wanted to understand how often customers visited its website, logged in, modified their subscriptions, and more. With that data, Pet Circle could improve loyalty and retention by adding customer value rather than transactional value.
There are many ingestion tools to choose from, ranging from simple open-source software to more automated and lower-maintenance solutions.
Transformation and data warehouses
A data warehouse’s main function is to provide a central repository for sourced data and prepare it for reporting and analytics. A data lake is also helpful and recommended for all historical data, whether it’s used for immediate analysis or analysis later on. Choosing the right data ingestion tool makes it near effortless to move data from sources to repositories.
Open-source tools, like data build tool (dbt), can further simplify the process when coupled with connectors like Fivetran to transform data that’s been loaded into the warehouse.
“Looking at Pet Circle, the company first attempted to build a data stack itself. The complete project to get data from source through to destination to analysis was predicted to take two years. We were able to reduce that ingestion to about a week, and the project was completed in two months total,” says Ignatius Bourke, Alliances Manager, Technology Partners at Fivetran.
“We enable organisations to monetise their data by reducing the heavy lifting. You save the effort of three people, two years of work, and about $400,000 of a project scope by switching to Fivetran.”
The power of business intelligence (BI)
BI tools are the final component of a great MDS. Increasingly powerful and easier to use, BI tools allow users to access data insights from anywhere. Even more, they can be leveraged to facilitate more efficient teamwork, increase business agility, make sense of the outpouring of data, and better personalise marketing messages.
Pet Circle turned to Sisense for Cloud Data Teams for its BI tool. This platform empowered Pet Circle to simplify its complex data and transform it into a powerful analytics app.
“With Netflix and smartwatches, insights are delivered to where we are. We don’t have to think or even know about the so-called ‘alphabet soup’ that’s AI, BI, ML. It just tells us what movie it thinks we’d like to watch next or how long of a walk we’ll need to reach our steps goal. That’s all insights at the point of decision-making. And that’s what Sisense wants to bring to business,” Rohan points out.
“Now, with Pet Circle, Sisense was able to give the company a competitive advantage; the differentiation and future-proofing. Pet Circle has grown, it's expanded into markets, and it has confidence in its data. All of that has allowed the company to generate revenue, increase customer satisfaction, and maintain costs.”
7 benefits of a Modern Data Stack (MDS):
Reduced costs: An MDS can reduce data engineering costs by more than a whopping 90% by eliminating the need to build and maintain data pipelines or normalise data from denormalised APIs.
Increased productivity: An MDS allows your data team to be more productive because available data increases without consuming in-house resources.
More data projects: With more time and more data, your team can focus on new analytics projects.
Extra time: An MDS will drastically decrease report generation time and ensure reports are up-to-date, saving your company time.
Better data reliability: The burden of extract, transform, load (ETL) maintenance will be eliminated and data reliability will improve with an MDS.
Improved data literacy: Intuitive and easy-to-use, modern BI tools like Sisense are designed to make data accessible to business users and technical employees alike.
Creation of new metrics: Additional data sources and a simple-to-use BI tool allows business to create a host of new metrics. This is made possible in two ways: by richer data that enables new types of cross-analysis and by greater data access across departments, which allows more employees to propose new metrics based on their specific competencies.
Sisense goes beyond traditional business intelligence by providing organisations with the ability to infuse analytics everywhere, embedded in both customer and employee applications and workflows. Sisense customers are breaking through the barriers of analytics adoption by going beyond the dashboard with Sisense Fusion - the highly customisable, AI-driven analytics cloud platform, that infuses intelligence at the right place and the right time, every time. More than 2,000 global companies rely on Sisense to innovate, disrupt markets and drive meaningful change in the world. Ranked as the No. 1 Business Intelligence company in terms of customer success, Sisense has also been named one of the Forbes’ Cloud 100, The World’s Best Cloud Companies, six years in a row. Visit us at www.sisense.com and connect with us on LinkedIn, Twitter, and Facebook.
Shaped by the real-world needs of data analysts, Fivetran technology is the smartest, fastest way to replicate your applications, databases, events and files into a high-performance cloud warehouse. Fivetran connectors deploy in minutes, require zero maintenance, and automatically adjust to source changes — so your data team can stop worrying about engineering and focus on driving insights.