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Data Summit: IT Execs Share Insights on Taking Analytics to the Cloud

Author: Tom Hoblitzell | | June 1, 2023

 

Datavail participated in a Data Summit 2023 session a few weeks ago in Boston where Data and Analytics, especially harnessing the value of the cloud and how it can accelerate improved decision-making, was front and center.

What Were the Key Takeaways From the Cloud Analytics Session I Held with IT Executives?

Takeaway 1: Moving analytics to the cloud provides more flexibility, scalability, and efficiency. The participants in the session unanimously agreed that migrating analytics to the cloud offers businesses unprecedented flexibility, scalability, and efficiency compared to on-premises solutions.

The cloud provides a level of expandability and scalability that is often overlooked. By compressing and expanding resources on an as-needed basis, you can optimize your infrastructure and better meet the demands of your analytics workloads. Furthermore, the cloud offers a broader range of virtual machines and capabilities that can enhance your organization’s analytical capabilities.

Takeaway 2: Ensuring data quality is crucial for successful cloud analytics implementation. The holy grail for most organizations is a “single version of the truth” which requires data quality, achieved by best practiced and consistent data preparation and validation.

Implementing robust data validation techniques during the data ingestion process is essential to ensure the accuracy and reliability of your analytics insights. Without accurate and clean data, your efforts may lead to misleading or unreliable results. Prioritizing data quality is key to unlocking the true potential of cloud analytics.

Takeaway 3: Adopting cloud analytics can lead to improved collaboration and cost efficiency, including flexible economic models, rapid deployment, reliability, high availability, and disaster recovery capabilities.

Migrating to the cloud enables your organization to keep pace with the rapidly evolving technology landscape, fostering agility and responsiveness to changing market conditions. Furthermore, embracing cloud analytics allows for innovation and the rapid deployment of new ideas and models, such as AI and machine learning, without the burden of extensive infrastructure deployment.

Additional Insights Surfaced:

  1. Cloud analytics provides more flexibility, scalability, and the ability to store different types of data compared to on-premises analytics.
  2. The cloud enables businesses to become more data-driven and solve business problems more efficiently.
  3. Organizations are moving to the cloud at a faster pace than predicted, with a majority of companies expected to have their analytics in the cloud by 2023.
  4. Data quality is crucial for successful analytics, and having a strong data foundation is key to achieving better insights.
  5. Concerns about security and costs are factors that make people hesitant to move to the cloud, but cloud providers offer robust security measures and can be more cost-efficient in the long run.
  6. The cloud allows for more innovation and rapid deployment of new ideas and models, such as AI and machine learning.
  7. Self-service BI and analytics are becoming more popular, with the cloud enabling easier access to data for business users.

One attendee in the audience said it best in commenting, “The cloud provides more flexibility because I don’t have to deploy it. I can very quickly put something in the cloud, see how it operates like a model of AI, and then turn around and say, let me make the adjustments.”

The cloud empowers you to experiment, iterate, and optimize your analytics initiatives without the constraints of traditional on-premises infrastructure.

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