How Digital Natives Can Transform Messy Data into Business Success

Elly Juniper, Media & Entertainment and Digital Native Business Sales Leader for Databricks Australia and New Zealand, is in a front-row seat observing how born-digital companies are making the leap to being truly data-driven by leveraging analytics and AI at scale. Here, she shines the light on five digital native companies from Asia-Pacific that have leveraged Databricks Lakehouse to spur business growth with a cost-efficient and resilient modern data platform.

Data and artificial intelligence (AI) are at the forefront of business-critical decisions. From data-savvy digital natives to ‘traditional’ enterprises, these companies know that in order to outpace competitors and delight their customers, they need to look ahead using data in real-time to predict and plan for the future, and not spend time looking back.

Talking to hundreds of customers has given us insight into why businesses are moving away from warehouses, on-premise software, and other legacy infrastructure. To achieve greater speed to market, they are also recoiling from building everything in-house from the ground up to adopting ready-to-use platforms. They’ve realised that in order to scale quickly, they need technology that is agile enough to manage the volume of data that comes with growth. By implementing Databricks Lakehouse as part of their modern data stack, digital-native businesses have shown they can scale for growth and stay uniquely connected to their customers by putting data in the hands of every team member.

As we emerge from the pandemic, digital transformation is no longer just about competitive pressure. It’s now the difference between success and failure. A digital native company needs a platform that will enable them to scale as their business grows, speed up their go-to-market iteration, and boost the efficiency of their teams to drive even more revenue and profitability. This means being bold in their choice of a multi-cloud data platform that is simple to use, with the unique ability to ingest data in a variety of formats (structured and unstructured) all in one place, as well as allowing for the evolution of their data and analytics strategy without lock in.

Here, we take a look at some digital native companies from across Asia-Pacific that leverage the Databricks Lakehouse platform to scale up their business and spur growth through data-driven decision-making.

Unifying data in one place to increase efficiency

Shift is a fast-growing, fintech company making it simple and convenient for Australian businesses to access capital. Speed is central to Shift’s business goals, but processing large volumes of banking data and customer records was slowing the company down. By implementing Databricks Lakehouse into their technology stack, Shift has centralised its data sources in one unified, scalable place to uncover meaningful insights more efficiently. With the information stored in Delta Lake, the company now provides personalised assessments and recommendations to its clients, dramatically improving the customer experience. And with the ability to expedite the full machine learning lifecycle, Shift can process data 90% faster than before, increasing its time-to-market by 24X for new solutions while boosting its predictive capabilities.

Using AI to complement how people work, not to replace them

Bigtincan is an Australian-based sales enablement provider that uses AI and ML to help businesses enhance sales productivity and customer engagement. Across its suite of AI-fueled solutions and extensive interactions with customers, Bigtincan was generating siloed data that restricted how it could provide insights and business intelligence to its clients. The company turned to Databricks Lakehouse to build a unified platform for data and AI that supports cross-collaboration betweens its global team. Particularly, it allowed for its data scientists access to real-time data to generate consolidated reports and personalised product recommendations for clients – all driven by ML. This has led to a 27% improvement in Bigtincan’s customer adoption rates, with clients receiving more relevant recommendations that drive higher conversion rates.

Hivery is an Australian-based AI category management optimisation company providing AI and ML-driven solutions for retailers and CPGs to increase sales, reduce costs, and maximise productivity. Leveraging Databricks Lakehouse has enabled the brand to take advantage of its customers’ retail data concisely and securely, allowing Hivery to accurately construct real-time visual representations of data to enable their clients to conduct scenario planning of product assortment and space in vending machines and at the store level. This improved the efficiency of its data teams, effectively allowing the company to onboard more customers in a shorter time.

Helping to foster team collaboration

Vonto uses AI to curate key insights for SMEs and tech startups in Australia to give them a holistic view of performance and key business indicators so that they can make more informed decision-making. With the help of Databricks Lakehouse, Vonto is able to scale up its capabilities to work on more complex datasets and advanced modelling, empowering the company to deliver even more engaging and actionable insights to its customers. Databricks also helped to improve the efficiency of Vonto’s in-house data team by providing a unified data platform that allowed better cross-collaboration between its data and product teams and to harness AI-powered solutions for their customers.

Making AI an essential part of business growth

The largest online-to-offline platform in Southeast Asia, Grab, needed to enable a consistent view of millions of its users to accurately forecast consumer needs and preferences from its six billion transactions across transport, food and grocery delivery and digital payments. Grab used Databricks Lakehouse to build a Customer360 platform that delivers these insights at scale, democratizing data through the rapid deployment of AI and BI use cases across their operations.. Today, data teams at Grab can collaborate, experiment and develop more innovative features to continually enhance consumer-centric experiences.

Start your Lakehouse journey

For these companies and 7,000 others, Databricks Lakehouse has provided a scalable, predictable framework that lowers risks and total cost of ownership, setting the foundation for long term success with data, analytics and AI at the core of their business innovation. And with Databricks Ventures, we’re powering the next wave of innovative AI-driven companies and technologies, so the lakehouse ecosystem can flourish and benefit more companies than ever before.

To kickstart your journey towards the future of scalable AI and analytics, tune in to hear about the data journeys of Australian digital natives Cascade and Liven, or how DoorDash and Grammarly have spurred their business growth with the help of the Databricks Lakehouse.

The post How Digital Natives Can Transform Messy Data into Business Success appeared first on Databricks.