Post-COVID: Times Driven by Data Analytics and Intelligence
4565
Of your peers have already read this article.
1:30 Minutes
The most insightful time you'll spend today!
As we think about economic recovery from COVID-19—both inside Google and outside through working with Google Cloud customers—we’ve made many important observations. Among them is the recognition that the ways software developers and IT practitioners work together will shift in the post COVID-19 world. Our economic recovery today will look different than past recoveries, and on a fundamental level, the way we innovate will be different than it’s ever been before.
Right now, we’re entering a new phase of cloud computing, where businesses have shifted from making tactical infrastructure decisions, to making larger IT decisions with an eye towards enabling transformation throughout the company. Data, and what we can do with that data, is key to this transformation. And how companies put data in the hands of every employee to help catalyze transformation and solve the most important and impactful opportunities in their industries is at the core.
A recent Google-commissioned study by IDG highlighted the role of data analytics and intelligent solutions when it comes to helping businesses separate from their competition. The survey of 2,000 IT leaders across the globe reinforced the notion that the ability to derive insights from data will go a long way towards determining which companies win in this new era.
Data analytics and intelligence were prioritized during COVID-19
The results of the IDG study show a separation amongst those organizations that embrace the capabilities of today’s data analytics and AI/ML tools and those that do not. When COVID-19 hit, many organizations cancelled IT initiatives, with 55% of respondents delaying or cancelling at least one technology project. However, 32% of respondents accelerated or introduced initiatives around building out or improving the use of data analytics and intelligence. IT leaders realize how critical data is to their future success, even when resources are scarce.
Digital-focused companies are faster to embrace advanced intelligence tools
Furthermore, enthusiasm for big data analytics, AI, and ML technologies is highest among companies who are further along in their digital transformation journeys. Fifty-four percent of companies who identify as “Fully digitally transformed” or “Digital native” are using or considering using these tools, vs. the global average of 37%. And, these same organizations are embracing the promise of AI more than their peers. Forty-eight percent felt that “Embedded AI across our full stack of cloud solutions will be critical” vs 39% of digital conservatives. These companies realize these digital tools enable them to be more resilient, agile, and prepared for whatever the future brings.
Companies are turning to cloud to maximize insights from data
As companies tap into the promise of data analytics and AI/ML, they are turning to cloud for help. When considering which cloud providers to work with, 78% of respondents said big data analysis is a “must have” or a “major consideration,” which placed this capability at the top of the list of consideration factors. This is not surprising, as cloud solutions address the most common pain points and barriers to innovation. Three of the respondents’ top four areas impeding innovation are addressed by cloud: Insufficient IT & developer skill sets (1st), security risks and concerns (2nd), and legacy systems and technologies (4th). Plus, cloud makes it easier to quickly launch a project, scale up or scale down, and pay for only what you use.
COVID-19 changed the very nature of business, and of IT. It forced IT leaders to decide where to put their scarce resources and big data analytics and AI/ML were, understandably, at the top of the list. To learn more about the findings, download the IDG report “No turning back: How the pandemic reshaped digital business agendas.”
5054
Of your peers have already watched this video.
2:50 Minutes
The most insightful time you'll spend today!
FedEx Ground Makes Talent Recruitment More Effective with AI
FedEx Ground is a package shipping company and is a subsidiary of FedEx. It wanted to make hiring easier, and more intuitive so that it could hire the best people.
“We need to have every advantage we can to recruit and retain talent. That’s what led us to the work with Google and its capabilities,” says Matt Tokorcheck, VP, Operations, Support and Engineering, FedEx Ground
The challenge was the narrow slotting of job roles. The openings were listed under specific headings which revolved around job types or departments–and if applicants didn’t fit or understand those categories, they didn’t apply.
Take, for example, applicants that came from the military. “Many of my fellow service members and veterans expressed difficulty in finding a job post the military because a lot of the skill sets that they’ve developed and honed over their military career aren’t as useful in the civilian world,” says David Henderson, Industrial Engineer, FedEx.
So FedEx Ground decided to work with Google Cloud’s AI-powered talent solution.
“As a job seeker when you come to our career site to search for jobs, that search is powered by Jibe and the Google Jobs API. And it really matches the keywords that a job seeker inputs with the jobs that are available at FedEx Ground, says Shailesh Bokil, MD, Talent Acquisition and Planning, Fedx Ground.
This makes job hunting a very intuitive experience for applicants.
“When I type into the search bar, I was immediately prompted to input my MOS, which is your military occupational specialty. And what it (the system) does is it takes the skills that are developed while serving in that MOS0 and matches them with skill sets that employers are looking. When I input 12A (an MOS), immediately I was getting results back for various engineer positions.
To find out more about how FedEx Ground employs AI-powered talent solution, watch the video.
1119
Of your peers have already watched this video.
29:16 Minutes
The most insightful time you'll spend today!
Navigating the AI Landscape: The Future of AI for ML Engineers
A podcast-style video series exploring how AI is shaping our future and how to prepare for changes. Developer advocate, Arwen Hauzhenga, shares his 10+ years of experience in machine learning and generative AI. He discusses the evolution of the field from data mining to data science and large-scale machine learning.
The video contains:
✦ Key developments in AI witnessed over the years
00:00
✦ Democratization of AI is making it more accessible to non-specialists
03:58
✦ AI and ML are leading towards worry-free infrastructure for model training and deployment
08:11
✦ Key pointers for building responsible AI systems
11:53
✦ Identifying the right use case and leveraging capabilities are crucial for successful AI implementation
15:33
✦ Learning machine learning doesn’t require being an expert
19:04
✦ Identifying the right use case and aligning with stakeholders is key to successful AI implementation
22:22
✦ Interacting with technology is changing significantly with AI
25:37
6082
Of your peers have already watched this video.
48:30 Minutes
The most insightful time you'll spend today!
Can Your Data Warehouse Handle a 100-Trillion Row Query?
Today’s enterprise demands from data go far beyond the capabilities of traditional data warehousing and for many leaders, the need to digitally transform their businesses is a key driver for data analytics spending.
Businesses want to make real-time decisions from fresh information as well as make future predictions from their data in order to remain competitive.
In this video, Jordan Tigani, Director of Product Management, Google BigQuery reveals the power of Google Cloud’s modern data warehouse, BigQuery, that helps businesses make informed decisions quickly.
In addition, he talks about how big Google BigQuery can get. He shares examples of how one customer ran a query against a giant table of 100 trillion rows. “I think it was something like 19 petabytes of data scanned. It took about took about 20 minutes. It used 39,000 slots, which is about 20,000 cores,” says Tigani.
He also shares examples of how businesses, such as online retailer, Zulily generate real business benefits from being able to query large datasets faster, and more easily than ever–without having to invest time managing infrastructure.
Finally, Amir Aryanpour, Technical Architect, Channel 4, talks abouut how connecting connecting Google BigQuery to other solutions with the Google Cloud Platform, including storage, data visualisation, and a sentiment analysis engine, among others, helped the company.
3108
Of your peers have already watched this video.
21:30 Minutes
The most insightful time you'll spend today!
How Google Cloud is Fortifying the Social Safety Net
The COVID-19 crisis is triggering both immediate and longer-term challenges for state and local governments.
In this video, Denise Winkler, Strategic Business Executive, Google Cloud and Jennifer Ricker, Assistant Secretary – Illinois Department of Innovation & Technology (DoIT), discuss a number of challenges and solutions around the pandemic.
First, they outline the programs that constitute the social safety net and the impact that COVID-19 has had on the social safety net and citizens. Then they share the Google Cloud solutions that have been mobilized to assist these agencies.
Ricker will also share how Google Cloud Contact Center AI supported the Illinois Department of Employment Security.
Finally, they talk about how Google Analytics can help communities open and recover.
Learn how Google Cloud is enabling public officials to gear up to meet unprecedented demand for unemployment and social services programs, launch expanded digital services, and more.
3088
Of your peers have already watched this video.
20:30 Minutes
The most insightful time you'll spend today!
How Visual Inspection AI Transforms the Manufacturing Industry
The pandemic has created demand volatility and has placed lots of pressure on manufacturers. Decreased demand for new products, the disruption of retail channels, and interruptions to supply chain operations have made it very challenging for manufacturers to operate profitable businesses.
This has left manufacturers keen to decrease costs and improve work efficiency by automating many of their work processes.
And many are discovering that visual inspection utilizing AI can help.
This video, hosted by Ying Fei, Product manager, Google Cloud and Sudhindra K Ghanathe, Industry Solutions Lead of Accenutre Google Business Group, Accenture, showcases how world-leading manufacturing companies use visual inspection AI to transform their business. Customers such as Siemens share how they use Google visual inspection AI to automate quality control process, achieve cost savings, and improve work efficiency.
More Relevant Stories for Your Company
Improved TabNet on Vertex AI: High-performance, scalable Tabular Deep Learning
Data scientists choose models based on various tradeoffs when solving machine learning (ML) problems that involve tabular (i.e., structured) data, the most common data type within enterprises. Among such models, decision trees are popular because they are easy to interpret, fast to train, and can obtain high accuracy quickly from
Siemens: What Smarter New Age Recruiting Looks Like
Siemens aims to shape the future—and has the scale, culture, and know-how to realize its ambitions. The Germany-headquartered industrial manufacturing business operates in more than 120 countries and focuses on electrification, automation, and digitalization. Siemens' extensive portfolio includes industrial production digitalization and automation technologies, diagnostic and therapeutic imaging for healthcare, and
VCP Peering and Private Endpoints on Vertex AI to Better Security and Predictions in Near Real-time
One of the biggest challenges when serving machine learning models is delivering predictions in near real-time. Whether you’re a retailer generating recommendations for users shopping on your site, or a food service company estimating delivery time, being able to serve results with low latency is crucial. That’s why we’re excited
Streamline Your Business Processes with Google Cloud’s Custom Document Splitter
Businesses rely on processing an inflow of documents to drive processes and make decisions. Many such documents are combined into a single file. For example, a loan application may have a driver’s license, paystub, W2, bank statement, and other document types within a single file. The complexity of handling many
