1. To begin with, what do you believe are the major shifts that businesses may expect while embracing data analytics in their digital transformation journey?

 

• As businesses accelerate their digital transformation journey, it has brought a significant shift in how leaders think and use the cloud for areas such as data analytics. Organizations are increasingly adopting cloud data warehouses or lakes to manage increasingly massive data sets and looking for cloud-enabled analytics solutions. Aside from addressing the shortcomings of on-prem data warehouses, moving data to the cloud enables organizations to get timely insights in a few minutes – thereby enabling enterprises to respond and adapt quickly to changing macroeconomic factors.
• Similarly, organizations that invested early in data analytics are now reaping the rewards of their investments and increasingly recognize the need to democratize and scale data analytics capabilities across the organization. By equipping workers with self-service analytics tools, workers can be empowered to get the insights they need from their data whenever they need it. Working with data will become less daunting to non-data-specialized employees, and the power of data-driven insights will rest in the hands of many, not just the data scientist teams.

If the pandemic has taught businesses one thing, it has got to be that ‘if you are not a digital business, you could be out of business”. A key tenet of a digital business is the ability to democratize data, and analytics and automate as much as possible so that data enables not just the technical hyper-experts but anyone who has to put data to work.

 

2. How can organizations use data analytics to drive operational efficiencies and reduce costs?

• Enterprises with a data-first business strategy and culture are known to be “Analytics Experts”, and they are more likely to outperform their peers in key business priorities. According to the Alteryx-commissioned IDC “Toward Analytic Automation in the Asia Pacific” research study, these “Analytic Experts” are more likely to outperform their peers in cost reduction by 56 percent.
• In the case of enhancing operational efficiencies, we can look at NTUC Income as an example of how data analytics helped the organization drive operational efficiencies. NTUC Income’s actuarial team was troubled by inefficient data analytics processes that hindered their ability to deliver insights to internal
• stakeholders in a timely manner. Firstly, silos of data processes resulted in data reconciliation issues in analysis and reports; and secondly, legacy data processing tools forced analysts to spend significant time manually generating data insights. NTUC Income worked with Alteryx to create the ideal data architecture that helped eliminate mundane data preparation tasks and improve operational efficiencies.

3. What is Alteryx's value proposition in ASEAN? How would it benefit ASEAN nations' businesses in the long run?

• With a combined GDP valued at US$3.2 trillion, ASEAN is the fifth-largest economy in the world and is poised to see further growth and development in 2022. ASEAN has the potential to leapfrog to the forefront of the global economy, thanks to accelerated technological growth, new trade opportunities from the Regional Comprehensive Economic Partnership, and new market opportunities in its emerging markets.
• However, the gap in data literacy threatens to hold back ASEAN businesses and impede the region’s aspiration to become a global economic leader. Alteryx provides ASEAN with the opportunity to leverage data analytics with ease and bridge the gap in data literacy. Its low-code/no-code AI-enabled analytics solutions automate complex and tedious business processes. It provides employees, who have no background in data analytics, the ability to easily self-learn data analytics and derive insights from data.
• Another key challenge that ASEAN businesses are now facing is not having enough data scientists and analysts to keep up with it all. Most of these organizations have tried to solve this problem by hiring more specialists which are already in short supply in recent years.  Alteryx’s end-to-end data analytics automation platform can bridge the technical capability skills gap, empowering employees to be citizen data scientists by breaking the data barrier and allowing them to deliver insights confidently and efficiently.

4. How does Alteryx help companies manage data quality and information governance?

• As organizations democratize data and access to analytics across all business functions, they can still retain information control with governed self-service analytics. For example, Alteryx’s solutions provide a simple drag-and-drop interface that serves as a visual audit trail for transparent decision making – enabling teams to be able to use certified, auditable, and reusable analytics assets.
• With Alteryx Designer, any user who interacts with data can use Designer Cloud to prep, blend, and output data in a highly visual, code-free way – enabling users
• To check and efficiently prepare data, a task that would previously take teams days to do can now be done in a few hours.

 

5. Tell us more about the session that Alteryx will be hosting at the show. What can attendees expect to gain from it?

Organizations understand the payoffs of a data-driven culture and want to make more decisions fueled by data and analytics. However, few have achieved breakthrough success. Complex disparate data silos, a lack of data and analytic talent, inefficient and manual processes, and a lack of data literacy have been key inhibitors holding them back. To unlock the benefits of a data-driven culture, it needs to start with people and a people-centric approach. The next-generation self-service analytics tools empower the workforce to work with data and gain insights on their own. Achieving a data-driven enterprise will become attainable by democratizing analytics across the organization.

Through the session ‘Scale the Impact of Analytics Across the Organization’, my colleague Vincent Toh will shed insights on the divide between people and technologies, the pathway toward analytics maturity, and how upskilling knowledge workers bridge the gap towards achieving data analytics capabilities for all. It will be this Analytics for All environment that will truly provide a democratized setting that provides data and analytics accessible anywhere and at any time, all within a tight governance framework.