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Should You Move Your Data Analytics to the Cloud?

Author: Tom Hoblitzell | | September 1, 2021


If you’re like many IT professionals, you’re finding that moving some or all of your systems to the cloud makes sense. Should you move your data analytics to the cloud?

What Do You Want from Your Data Analytics?

We’ve done research on this question, and we’ve found that there are a variety of things businesses want:

  • Self-service data exploration and discovery-oriented forms of advanced analytics
  • Data integrated into a single, trusted data store
  • Answers to any question across business processes
  • Both new and traditional data, thereby enabling analytics correlations across all data
  • Low total cost of ownership (TCO)
  • A 360° view of any person or organization that touches the company
  • Systems to respond quickly and cheaply to changes in business conditions or acquisitions
  • Scalability
  • Fast response

You’ll notice a couple themes coming through from the answers we’ve received. They relate to low cost, scalability, quick and agile systems to produce analytics, and a desire to have analytics that consider input from across the organization.

How the Cloud Meets Your Data Analytics Wish List

Moving your data analytics to the cloud helps to address the wish list we received during our research.

  • Low Cost. We always recommend that you align your cloud adoption costs with your expectations. But when managed properly, moving to the cloud is a money saver.
  • In many instances, businesses find that as they move through the states of business intelligence maturity, and as their companies grow, they need more space and/or power. The cloud is easy to scale.
  • Quick and Agile Systems. You’ll find that analytics in the cloud run on fast processors that can run extremely agile analytics.
  • Organization-Wide Analytics. Since it’s easy to give a variety of employees access to analytics in the cloud, it’s easier to bring together analytics correlations across data from every corner of your organization.


Many individuals responsible for creating or using data analytics have discovered that analytics in the cloud helps them to meet their goals and grow their businesses.

Are There Challenges in Moving Data Analytics to the Cloud?

There are challenges, but none that can’t be overcome. Putting analytics in the cloud isn’t a “lift and shift” task; you need to tailor your move to your own organization. Here are some of the issues to consider.

Your Organization’s Business Intelligence Maturity

Your use of analytics will vary depending on how your organization understands the use of business intelligence (BI). There’s a business intelligence maturity model that describes how your business will evolve in terms of using analytics.

In the first stage, your staff will only be interested in analytics that help them run the business. They will want to know what happened in the business such as how many widgets were produced in a certain amount of time. In the second stage, you will be providing dashboards for your executives to track performance on a regular basis.

The third stage will find you looking at the dashboards for operational and financial perspectives to determine how they drive one another. In the fourth stage, you’ll start using analytics to research new methods and technologies that will help you progress.

The fifth and final stage comes after your organization has mastered the learning curve. You’ll start employing analytics to define strategy, and you’ll also start using artificial intelligence, machine learning, and other more advanced tools. You’ll be innovating, increasing productivity, and differentiating your business through market agility.

Technical Challenges

After migrating your analytics to the cloud, you’ll need to keep up with a rapidly changing tech environment, and resolve issues such as security, ethics, privacy, and data quality. You’ll also need to start integrating multiple data sources and training your organization on how to use analytics in order to provide insights that are truly useful for consumers and front-line workers.

Key Vendors

Snowflake and Redshift are the two prime database technologies at this point. Snowflake is a SaaS data platform that offers faster, easier to use, and more flexible analytics over many others. Amazon Redshift is a data warehouse service that can be integrated with BI tools.

Why Move to the Cloud?

Before moving to the cloud, you’ll need to follow a set of best practices. But, once you get there, you’ll find a wide range of benefits. You can increase your flexibility and scalability, reduce capital expenditures, and improve your decision making using leading-edge tools.

Datavail can help because we have the expertise and experience to help you enable systems that provide the insight you need to drive business value. For more information about BI and data analytics in the cloud, download a copy of our white paper, A Panoramic View of Cloud Analytics: The Insight You Need to Grow Your Business.

In this white paper, you’ll find more information about technical challenges, key vendors, and best practices. You’ll also see three case studies that Illustrate how other businesses are transforming due to data analytics in the cloud.

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