How a Modern Cloud Analytics Stack Can Optimize the Value of Your Data

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Read more about author Nahla Davies.

Data is vital when it comes to growing a business, but many organizations fail to utilize it properly once it has been collected. At the same time, many forward-thinking businesses, from startups to large corporations, have implemented a modern cloud analytics stack to use data more efficiently. 

In this article, we will discuss how a modern cloud analytics stack can optimize the value of your data and help you make better decisions that can result in growth. 

What Is a Modern Cloud Analytics Stack?

A modern cloud analytics stack (also referred to as a modern data stack or MDS) comprises three layers of technologies and tools that allow businesses to collect, store, and analyze data effectively. 

The first stack relates to automated data integration, the second focuses on storing data within a cloud warehouse, and the third delivers modern business intelligence tools. Together, these stacks not only deliver speed and security but also help focus your business on the things that matter, like reducing costs, saving time, and reallocating resources. 

Although technologies constantly change, a modern cloud analytics stack will maintain the same data life cycle using a cloud-native data platform: 

  • Data ingestion
  • Transferring data to a cloud data warehouse
  • Data integration
  • Data transformation – ETL (extract, transform, load)
  • Business intelligence layer 
  • Reverse ETL
  • Event tracking

What Are the Key Benefits of a Modern Cloud Analytics Stack?

A modern cloud analytics stack (MDS) helps organizations to:

  • Reduce IT constraints, including maintenance and physical storage
  • Streamline data and IT teams
  • Improve the accessibility of data
  • Speed up data processing
  • Integrate both first and third-party data
  • Establish more privacy control 
  • Implement better data governance

A modern cloud analytics stack can also work alongside machine learning APIs to create advanced performance analysis models and identify market opportunities. Because of this broad compatibility, modern data stacks can easily adjust to new technological advancements and future-proofing processes within the business. 

7 Ways a Modern Cloud Analytics Stack Can Optimize the Value of Your Data

We have already outlined some benefits of a modern cloud analytics stack. However, the most important aspect of this article is how data and analytics can be better optimized to ensure your business can make the best possible decisions. 

Let’s consider seven ways a modern cloud analytics stack can optimize the value of your data to achieve better results.

1. Reduces Data Engineering Costs

An MDS can help to reduce data engineering costs by around 90% in some instances, reducing the need to build and maintain extensive data pipelines or attempt to normalize data collected from denormalized APIs. The term normalizing data refers to organizing disordered data into usable internal databases.

Within a modern stack, the data connectors are already initialized in what is effectively a “plug-and-play” setup. This enables them to be launched in a matter of minutes and deliver ready-to-query data to a chosen destination. 

For example, an MDS is a much more effective option if an organization wishes to centralize its data instead of reallocating in-house resources to transfer data into an existing SQL server warehouse. An SQL transfer can take around two years, requiring a designated data engineer, numerous human resources, and of course, significant expenditure. 

2. Increases the Productivity of Your Data Team

A modern cloud analytics stack allows data teams to be much more productive, expanding available data without requiring significant in-house resources. 

Many businesses currently rely on manual ETL (extract, transform, load) processes, which limits the number of data sources that can be centralized. This can include laborious tasks such as extracting data into an Excel spreadsheet. 

An MDS can significantly increase the number of usable data sources without the need for more human resources or time-consuming, manual processes. 

3. Allows You to Focus on New Analytics Projects

The obvious benefit of having more data sources and more time to process them is that you can launch new and ambitious analytics projects. A modern stack allows organizations to process data from their marketing channels instead of relying on third parties, allowing data teams to gain more insights and have more freedom. 

This is especially useful if the goal of analytics is to map out customer journeys. Access to all marketing data means successful and less productive channels can be easily identified. For example, your data team can compare whether the organic SEO spend is providing better results than paid acquisition. 

4. Helps Generate Reports Quickly

Implementing a modern cloud analytics stack can significantly reduce report generation times. Using an MDS, reports can be created on a regular basis, ensuring your workforce is always using up-to-date information. In many cases, report generation times can be reduced from days to a matter of hours.

Visually impressive reports can be produced by SQL, which can then be scheduled and emailed to relevant people via integrated tools such as Slack. This allows valuable insights to be shared quickly via an automated process. 

5. Improves Accessibility Across the Organization

The latest business intelligence (BI) tools are extremely simple to use and very intuitive, so anyone across the organization can access data easily, even if they have limited technical knowledge. 

Without the tools provided by a modern data stack, businesses had a reduced data flow, with sales teams sometimes having to liaise with technical teams to find what they were looking for. As more people within the organization actively interact with data, the likelihood of new ideas and strategies being put forward increases.

6. Provides More Reliability

Data reliability is greatly improved with an MDS, with infrastructure downtime and maintenance eliminated thanks to the cloud platform. Organizations can create automated data pipelines that automatically consider changes to APIs or schemas. As a result, your data team can work effectively without worrying about potential pipeline failures or missing data. 

7. Gives You Access to a Broader Range of Performance Metrics

With access to a wide range of data sources and better data visibility across the business, analysts can define new performance metrics, such as cross-analysis and metrics that focus on individual teams or team members.

By using a modern cloud analytics stack, sales data can be replicated in the cloud data warehouse to help build dashboards that define key performance indicators. This is one of the hundreds of examples of how abundant and fluid data can be used to improve business operations. 

Wrapping Up

A modern cloud analytics stack is the future of data, substantially increasing the amount of data that can be collected and improving how it is processed and how easily it can be shared across a business. 

The three stacks (collection, storage, and analysis) save time and resources, while cloud hosting reduces the need for physical infrastructure that has to be continuously maintained. As the speed of data normalization and report creation increases dramatically, your data team can work much more effectively, allowing them to create new performance metrics and explore new projects. 

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