The formula for growth and innovation: Big data and analytics | Techsauce

The formula for growth and innovation: Big data and analytics

Big data analytics is the process of examining large and varied data sets to uncover hidden patterns, unknown correlations, market trends, customer preferences and other useful information that can help organizations make more-informed business decisions.  At the Techsauce Global Summit, a panel of experts sat down to discuss what this means for businesses and how the use of big data can improve

Through technology, data collation has become a lot easier, and analysis has become a lot faster.  However, the fundamentals of statistics and statistical methods are still the same, which is to establish a strong hypothesis and test it.  Data scientist must ensure a good structure around the data and how to use it.  A solidly developed rationale for this is fundamental.

The question of how to establish rigor around the use of data and the analyzing of data was posed to the panel, and Dr. Amornvivate of SCB Abacus said that one of the fundamental problems faced when it comes to big data analysis is to find the right people for the job.  Data science is a relatively new field, and many tech people are very young, so there are no hard and fast proven cases to showcase their experience.  Also, the data sets that companies have to work with these days are huge and loaded with unnecessary data.  The challenge of sifting through the useful and useless data is the work of a domain expert, a position in an organization that is the hardest to fill.  And even now, with the inroads made in AI and machine learning innovation in the field of data analytics, companies still need the human element as machine learning can give you data regarding the correlation but not the causality.  Humans can only test causality, and that is the reason for ensuring that you hire the right people.  Experts in overlapping technologies will become precious human resources in the future.  Further, Araya of Snapcart expanded on that point by explaining that within their organization, they are looking for the “Unicorn Data Scientist.”  Snapcart ideally would like a person that knows data, business, and technology.  To hire a person that knows how to code, machine learning, and industry expertise.  To overcome this issue, Snapcart employs data scientist along with business intelligence analyst.  The expert knowledge of the individual compliments each other, as the data scientist, knows what to do and the business intelligence analyst knows analytics.

To implement a use-case, do you build or buy?

For Snapcart, they believe in both.  They look to creating what can benefit their core business, in the long run, looking at aspects such as sustainability and competitive advantage.  For example, OCR technology.  Snapcart tried to use platforms produced outside the company, but it did not work, as the service providers did not understand the in-depth scale of the problem.  Snapcart offers an online dashboard to their clients, where clients can view data analysis and consumer insights.  The design time to create a unique dashboard for each customer is extremely lengthy, Snapcart found that outsourcing this was the correct approach, as the company that provided the solution is much better at creating the dashboard than Snapcart.

SCB Abacus, on the other hand, prefers to build their technologies. Abacus is a small team that looks at scalability, flexibility and right use case to develop internally.  In no way are they not open to partnerships, but finding the right partner is not often easy.  For example, when it comes to machine learning, companies need to allow it to learn.  The reiteration and design of the product are crucial to make sure that companies have a product that they are confident to deliver.  In the field of finances, heavy regulation makes it difficult to have that process outside of the organization.

According to Dave or Nugit, it is important for companies to own and control their data.  It should be a core competency within an organization and data analytics should not be outsourced.  The platform used makes little to no difference, as long as companies own the setup and can manage the tool.

For Vachara from Computerlogy, he tries to develop internally with the customer in mind.  he prioritizes what the market needs and tries to deliver a particular product that is preconfigured so customers can use the insights.

Actionable insights

The panel concluded with a quick look at how to action ideas within companies. Some of the insights are as follows:

  • Less focus on infrastructure and protecting; more focus on interpreting and providing the data to the right people
  • Offline data was difficult to collect; act on the data in real time and optimize marketing spend
  • People do not articulate the right use-case; articulation is necessary, especially internally
  • Delivery of insights are important for a company; adoption of the insights are even more valuable for business.
  • Open up communication to all the relevant people in the company.

Panel: Sutapa Amornvivat, Ph.D. – CEO, SCB Abacus David Sanderson – CEO, Nugit Araya Hutasuwan – CFO, Snapcart Vachara Aemavat – CEO & Co-Founder, Computerlogy Moderated by Michelle Katics – Co-Founder & CEO, PortfolioQuest

ลงทะเบียนเข้าสู่ระบบ เพื่ออ่านบทความฟรีไม่จำกัด

No comment


Responsive image

iFLYTEK Reveals Keynote Session at Techsauce Global Summit 2024: Applying AI in the ASEAN Region

iFLYTEK presents a Keynote Session at Techsauce Global Summit 2024, decoding the growth of AI in Southeast Asia (SEA) and its global impact. Led by Mr. Roy Yao, Vice President of t...

Responsive image

SPACE-F Launches Batch 5 of Global FoodTech Accelerator and Incubator to Drive Innovation to Address Food Industry Challenges

SPACE-F Launches Batch 5 of Global FoodTech Accelerator and Incubator program that aims to foster innovative solutions to address current and future food industry challenges....

Responsive image