Following two action-packed days of workshops, conferences, paper presentations, and tech talks, Machine Learning Developers Summit 2023 concluded by awarding 40 dynamic data scientists with the 40 Under 40 Data Scientists award. Aakash is a seasoned analytics leader with 15 years experience and has been instrumental in driving data and insight-led transformations. Over his career, he has worked closely with biz functions to drive revenue and achieve aggressive market growth by leveraging more than 50 analytical approaches. He also has experience in launching AI and tech-based solutions like Omni Channel Attribution, Customer Segmentation, Customer-360, Supply Chain Efficiency, Workforce Management and more at telecom, media, FMCG, retail, and ecommerce industries. Abhilash Surendran is assistant vice president, analytics, and data science at Merkle, leading the analytics practise for their high-tech portfolio. He comes with 15 years of experience in advanced analytics, data science, data visualisation and consulting.

The analytics firm has released its top 10 data and analytics technology trends for 2020 that it says can help organisations prepare for a post-pandemic reset. "To innovate their way beyond COVID-19, data and analytics leaders require an ever-increasing speed and scale of analysis in terms of both processing and access to succeed," explains Rita Sallam, research vice president at Gartner. By the end of 2024, 75% of organisations will shift from piloting to operationalising artificial intelligence (AI), driving a 5x increase in streaming data and analytics infrastructures. "Within the current pandemic context, AI techniques such as machine learning (ML), optimisation and natural language processing (NLP) are providing vital insights and predictions about the spread of the virus and the effectiveness and impact of countermeasures," Sallam. "Other smarter AI techniques such as reinforcement learning and distributed learning are creating more adaptable and flexible systems to handle complex business situations; for example, agent-based systems that model and stimulate complex systems."

The massive data sets, complex processing capabilities and advanced analytical models in the current digital business landscape create the perfect storm of opportunity for data and analytics. After languishing for decades, graph approaches are being embraced by analysts, data scientists and data management professionals. Graph technology is a sort of catch-all phrase that includes graph theory, graph analytics and graph data management. IT executives have a growing interest in graphs, as there is a basic understanding that graph technology is somehow different from existing solutions. Data and analytics leaders are being asked to provide guidance regarding how graph technology can be used, but many still don't have a complete understanding.

When COVID-19 hit, organizations using traditional analytics techniques that rely heavily on large amounts of historical data realized one important thing: Many of these models are no longer relevant. Essentially, the pandemic changed everything, rendering a lot of data useless. In turn, forward-looking data and analytics teams are pivoting from traditional AI techniques relying on "big" data to a class of analytics that requires less, or "small" and more varied. Transitioning from big data to small and wide data is one of the Gartner top data and analytics trends for 2021. These trends represent business, market and technology dynamics that data and analytics leaders cannot afford to ignore.

When COVID-19 hit, organizations using traditional analytics techniques that rely heavily on large amounts of historical data realized one important thing: Many of these models are no longer relevant. Essentially, the pandemic changed everything, rendering a lot of data useless. In turn, forward-looking data and analytics teams are pivoting from traditional AI techniques relying on "big" data to a class of analytics that requires less, or "small" and more varied. Transitioning from big data to small and wide data is one of the Gartner top data and analytics trends for 2021. These trends represent business, market and technology dynamics that data and analytics leaders cannot afford to ignore.

In response to the COVID-19 emergency, over 500 clinical trials of potential COVID-19 treatments and interventions began worldwide. The trials use a living database that compiles and curates data from trial registries and other sources. This helps medical and public health experts predict disease spread, find new treatments and plan for clinical management of the pandemic. Data and analytics combined with artificial intelligence (AI) technologies will be paramount in the effort to predict, prepare and respond in a proactive and accelerated manner to a global crisis and its aftermath. "To innovate their way beyond the post-COVID-19 world, data and analytics leaders require an ever-increasing velocity and scale of analysis in terms of processing and access to succeed in the face of unprecedented market shifts," says Rita Sallam, Distinguished VP Analyst, Gartner. Here are the top 10 technology trends that data and analytics leaders should focus on as they look to make essential investments to prepare for a reset.

Gartner, Inc. identified the top 10 data and analytics (D&A) technology trends for 2020 that can help data and analytics leaders navigate their COVID-19 response and recovery and prepare for a post-pandemic reset. "To innovate their way beyond a post-COVID-19 world, data and analytics leaders require an ever-increasing velocity and scale of analysis in terms of processing and access to succeed in the face of unprecedented market shifts," said Rita Sallam, distinguished research vice president at Gartner. By the end of 2024, 75% of organizations will shift from piloting to operationalizing artificial intelligence (AI), driving a 5 times increase in streaming data and analytics infrastructures. Within the current pandemic context, AI techniques such as machine learning (ML), optimization and natural language processing (NLP) are providing vital insights and predictions about the spread of the virus and the effectiveness and impact of countermeasures. Other smarter AI techniques such as reinforcement learning and distributed learning are creating more adaptable and flexible systems to handle complex business situations; for example, agent-based systems that model and simulate complex systems.

Gartner, Inc. identified the top 10 data and analytics (D&A) technology trends for 2020 that can help data and analytics leaders navigate their COVID-19 response and recovery and prepare for a post-pandemic reset. "To innovate their way beyond a post-COVID-19 world, data and analytics leaders require an ever-increasing velocity and scale of analysis in terms of processing and access to succeed in the face of unprecedented market shifts," said Rita Sallam, distinguished research vice president at Gartner. AIBy the end of 2024, 75% of organizations will shift from piloting to operationalizing artificial intelligence (AI), driving a 5 times increase in streaming data and analytics infrastructures. Within the current pandemic context, AI techniques such as machine learning (ML), optimization and natural language processing (NLP) are providing vital insights and predictions about the spread of the virus and the effectiveness and impact of countermeasures.Other smarter AI techniques such as reinforcement learning and distributed learning are creating more adaptable and flexible systems to handle complex business situations; for example, agent-based systems that model and simulate complex systems. Dynamic data stories with more automated and consumerized experiences will replace visual, point-and-click authoring and exploration. As a result, the amount of time users spend using predefined dashboards will decline.

To help their organizations capitalize on artificial intelligence and analytics, CAOs must do more than demonstrate their technical chops. They need to lead like a Catalyst. The role of the chief analytics officer (CAO) is being thrust into the spotlight as artificial intelligence (AI) technology continues to improve--and prove its value. AI and other advanced analytics will unlock $9.5 trillion to $15.4 trillion annually, with recent AI advances such as deep learning alone making up nearly 40 percent of the total. Given the enormity of the stakes, it's no surprise that CEOs are asking their CAOs (or those assuming CAO duties under a different title) to deploy and scale AI and advanced analytics--stat. Yet while the opportunity is great, so too is the challenge.

The insights offered by Big Data are key to many businesses today. Getting the information that's hidden within it isn't easy but there are plenty of companies set up to help organisations do just that. Trifacta is one such company. It specialises in cleaning and preparing data, ready for it to be mined for key information, or train machine learning algorithms. One of its key products, Cloud Dataprep, makes use of Google's large cloud infrastructure footprint, which puts the data preparation tool in the hands of all manner of companies.