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محتوای ارائه شده توسط Virtualitics. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Virtualitics یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal
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How Intelligent Exploration Upskills Analysts

8:09
 
اشتراک گذاری
 

Manage episode 360080896 series 3364353
محتوای ارائه شده توسط Virtualitics. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Virtualitics یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

Organizations are striving to make data-driven decisions that will keep them ahead of the competition and position themselves for strong, healthy growth. They have vast amounts of data at their disposal that potentially hold the answers; they’re missing enough data science skill to extract those answers. The key to closing that gap is in the untapped potential of the data analysts. With the right tools and techniques, upskilled analysts can supercharge an organization’s entire data strategy.

According to a survey by PwC, "85% of business leaders agree that companies need to upskill their workforce significantly to meet the challenges of the digital age." The rate of change and a high degree of competition means that to get an advantage you need to stay ahead of your competition. Pivot faster and pivot sooner, because success is a matter of degrees.

I spoke at the Gartner Data and Analytics Summit, along with Virtualitics Head of Product Bryan Katis, about how Intelligent Exploration is the superpower analysts need to help them surface the answers that are hiding in your data and provide the insight that will drive successful strategies.

We surveyed data and data science leaders early this year and asked them how their teams could be more effective. They agreed that there’s not enough data science talent and that the lack of resources is holding back their exploration and overall AI strategy. They acknowledged that the data they’re putting so much effort and money into capturing, storing, and organizing isn’t being used effectively.

  continue reading

46 قسمت

Artwork
iconاشتراک گذاری
 
Manage episode 360080896 series 3364353
محتوای ارائه شده توسط Virtualitics. تمام محتوای پادکست شامل قسمت‌ها، گرافیک‌ها و توضیحات پادکست مستقیماً توسط Virtualitics یا شریک پلتفرم پادکست آن‌ها آپلود و ارائه می‌شوند. اگر فکر می‌کنید شخصی بدون اجازه شما از اثر دارای حق نسخه‌برداری شما استفاده می‌کند، می‌توانید روندی که در اینجا شرح داده شده است را دنبال کنید.https://fa.player.fm/legal

Organizations are striving to make data-driven decisions that will keep them ahead of the competition and position themselves for strong, healthy growth. They have vast amounts of data at their disposal that potentially hold the answers; they’re missing enough data science skill to extract those answers. The key to closing that gap is in the untapped potential of the data analysts. With the right tools and techniques, upskilled analysts can supercharge an organization’s entire data strategy.

According to a survey by PwC, "85% of business leaders agree that companies need to upskill their workforce significantly to meet the challenges of the digital age." The rate of change and a high degree of competition means that to get an advantage you need to stay ahead of your competition. Pivot faster and pivot sooner, because success is a matter of degrees.

I spoke at the Gartner Data and Analytics Summit, along with Virtualitics Head of Product Bryan Katis, about how Intelligent Exploration is the superpower analysts need to help them surface the answers that are hiding in your data and provide the insight that will drive successful strategies.

We surveyed data and data science leaders early this year and asked them how their teams could be more effective. They agreed that there’s not enough data science talent and that the lack of resources is holding back their exploration and overall AI strategy. They acknowledged that the data they’re putting so much effort and money into capturing, storing, and organizing isn’t being used effectively.

  continue reading

46 قسمت

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