22 November 2024, Fri |
11:06 PM
By Abboud Ghanem, Regional Vice President, Middle East and Africa, Alteryx
Alteryx, Inc. shares the company’s outlook for 2021 and guidance to help decisionmakers better strategize and leverage technology to suit individual business requirements.
The predictions focus primarily on key learnings from the past year, as well as anticipated trends and areas of clear business necessity. At the core of these forecasts, Alteryx identifies better use of data analytics and process automation, in addition to investments in upskilling as areas which are pivotal to aiding sustained growth in the digital age.
Like the much-publicized ‘digital divide’, an ‘analytic divide’ is also starting to emerge. Many companies were driven to invest in analytics due to the pandemic, while others were forced to cut anything they did not view as critical, simply to keep the lights on – and a proper investment in analytics was, for these organizations, one of the first items on the chopping block. This means that the analytic divide will further widen in 2021, and this trend will continue for many years to come. Without a doubt, the winners and losers in any industry will continue to be defined by those that are leveraging analytics and those that are not.
It is the job of the Chief Data Officer (CDO) to ensure expansion of growth across the entire business. This can be achieved by providing structured data that people can actually use. A successful CDO should democratize data so that it is accessible and understandable by people. A good CTO will complement the CDO by creating the necessary tooling to find the required data. This means giving users a set of visualization and reporting tools that allow them to identify trends and key learnings. The new year will bring closer collaboration between these two roles, driven by sheer necessity. If a business has tools with ‘bad’ data, data challenges are exacerbated. If there are limited tools, only a small subset can exploit that data for the good of the organization and the audiences it serves.
Using a powerful analytics platform that enables machine learning capabilities is crucial to detecting and addressing cybersecurity threats more rapidly, providing the ability to examine large volumes of data, identifying patterns and deliver actionable intelligence. With the further democratization of data, industries will witness citizen data scientists increasingly playing a key role in helping security teams enhance and simplify their cyber defense technologies by precisely detecting future attacks, proactively identifying security blind spots across the network and protecting valuable company information.
The work-from-anywhere concept has created an opportunity for CISOs to consider strategic approaches for managing non-traditional security risks. To accommodate this shift, corporate security departments will begin expanding the perimeter into employees’ homes to ensure that cyber risks are not unknowingly introduced into the corporate network. CISOs must work with HR teams to increase employee awareness of cybersecurity measures, proactively recognizing and reporting risks. CISOs adopting the zero-trust model will be able to improve secure access to corporate resources through continuous assessment and intent-based authentication policies.
While it is always important for companies to offer training to their employees, the fields of data science and digital transformation are challenging companies to break the mold and deliver new and constantly evolving ways to upskill and deliver ROI. Upskilling programs that help people learn and apply skills in real time will become more prevalent, where hackathons and other on the job experiences will use real data and issues to create genuine, required impact for the business. Data science has evolved to the degree where employees should not be required to pursue further education to understand a concept, they should be immersed by encountering new tools and technologies to meet current needs.
The pandemic has made it clear that the world still depends on robust manufacturing and supply chains. As businesses gear up not just to survive, but to thrive in the era of social distancing, predictive analytics will further emerge as a crucial tool for mitigating risks, managing volatility and offsetting risk. During the height of the pandemic, businesses saw their forecasting models and processes simply break down. With supply chains more complex and dynamic than ever, moving forward it will be crucial that they are augmented, automated and enhanced through the support of analytics processing that matches their sophistication.
COVID-19 forced organizations to address an enormous number of challenges and in doing so, drove an intense focus on data and analytics to provide much-needed insight. From genome sequencing and understanding the virus, its mutations and spread, to anticipating the needs of healthcare workers and managing the rollout of government aid – all of this was made possible by the analysis of data. With the virus also shedding light on other areas more improvement, organizations are now more acutely aware of how data analytics and automation can solve not only business, but also some of humanity’s greatest challenges.
“COVID-19 has rapidly accelerated the already growing dependence on data-driven technologies and forced companies across the Middle East and Africa to stop seeing data analysis as a niche activity,” said Abboud Ghanem, Regional Vice President, Middle East and Africa, Alteryx. “Data-based decisions continue to form the backbone of successful business strategies but requires an entirely new mind-set and skills-set to thrive in 2021. As more workforces look to work remotely, businesses must avoid lowering their guard and upskill human talent to make full use of data assets available to optimize and automate processes, maintain cybersecurity precautions and provide the actionable insights needed across the entire organization.”
