Democratise data science: The key to including SMBs in the machine learning equation
- 09 May, 2017 13:19
In the past two years we have heard that machine learning, predictive analytics and Artificial Intelligence (AI) will soon rule the world… and Australia. While this is exciting, today only a small part of Australian organisations with big budgets are really in the race for harvesting the benefits of the analytics era.
We recently saw Google acquiring Australian-born data company Kaggle, in an effort to improve its artificial intelligence and machine learning capabilities. A Centre for Artificial Intelligence hosted by the University of Technology of Sydney also opened earlier this year, with the aim of becoming a global hub for theoretical and applied research for machine learning.
While these are great initiatives, likely to position Australia at the forefront of the next-generation of the analytics scene, smaller organisations currently don’t seem to be part of the equation. This could have dramatic consequences for our entire economy as the future of business will be ruled by smart analytics, automation and intelligent or cognitive applications.
Democratise data science for SMBs
Smaller organisations have been trying to keep up with the pace of innovation in the data analytics and automation space. Many of them actually understand the potential of using data to optimise their business and win new customers, and they are well equipped to capture and store data from multiple sources. But they don’t really know how to exploit and make sense of that data, or just can’t afford it.
Data analysis is the first step towards a successful machine learning program. Without proper data science capabilities, SMBs will never be able to access the full potential of analytics nor participate to the AI revolution.
The problem is, SMBs don’t have millions of dollars to invest in advanced data science technologies, nor can they afford to hire armies of data scientists to analyse massive amounts of data and build advanced automation and predictive models.
An industry approach needed
While every organisation is focused on using technology to serve its own benefits, innovation is a collective effort and we need every organisation to join in.
SMBs’ struggle to afford the same technology or tech talent capacities as big corporations means that there is a responsibility, but also a business opportunity, for technology providers and major players in each industry to make data science accessible to smaller organisations.
As an industry, we should encourage SMBs to look into data science as a mean to improve their business and optimise their processes. We need to open the conversation, raise awareness about the benefits of data science, and help SMBs find ways to incorporate this element in their everyday operations.
Technology providers should also start to discuss the data question directly with non-IT staff, with an instructive approach. SMBs should be able to empower their line of business managers: marketing, finance, operations etc. It is important that these decision-makers understand what’s at stake and how they can become drivers of data science projects.
Making data science accessible to all parts of the business
For small and medium organisations, investing in the right platform is vital to make the transition from data to action. But there are so many solutions available, it is difficult to choose which platform to use.
Many companies end up piling up data mining and analytics platforms, combining them with app development add-ons, ultimately making the whole analytics engine overly complex and inefficient.
As technology providers, we need to offer platforms that can combine smart app development features and data analytics capabilities, and that can be used by both IT and non-IT staff. Line of business managers – CMOs, CFOs, COOs - should be able to build and deliver high-performing applications to their users through the same platform without needing coding skills. Additionally, IT teams should be able to easily plug in various data sources and back office systems to the same platform, so every part of the business communicates and deep learning can occur uniformly.
Decision-makers need specifically-designed analytics solutions to build, scale and protect mission-critical applications with cognitive capabilities that are flexible enough to continuously evolve with the business.
A new world of possibilities
SMBs need the right format, volume, and understanding of data before they can effectively deploy artificial intelligence solutions.
Using data science will help them gain valuable knowledge about their customers. It will also provide insights that can feed predictive tools to help with cash-flow management for example, but also optimise staff time thanks to automation, so they can focus on higher value tasks.
Technology vendors are starting to better understand this need and now provide SMBs with affordable tools to scale data analysis, thanks to advanced automation platforms, removing the need for an army of data scientists. It all comes down to removing the complexity so everyone in the business is empowered.
Mark Armstrong is vice president and managing director of international operations for EMEA and APJ, Progress Software.