How to Choose the Right Cloud Data Platform for Your Organization

The modern cloud data platform has become essential to any organization’s digital transformation strategy. The modern cloud data platform is a great way to manage your data, and it’s not just about storing data in the cloud. It also helps you make sense of that data by providing analytical tools so you can analyze what’s happening by leveraging your data.

The amount of data we generate grows exponentially every year; companies are looking for ways to harness all this data to gain increased insights. As organizations revitalize their cloud strategy, cloud data platforms (data warehouses) have become a necessary component. Cloud computing services like Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP) provide an easy way to access massive amounts of storage space and computing power. These services allow businesses to quickly scale up their data processing capacity as their needs grow.?

However, choosing an ideal cloud data platform can be challenging. The three primary cloud service providers (CSPs) offer different levels of support, pricing, and features, along with other vendors such as Snowflake and DataBricks. This article explores how to choose between these options based on your specific use cases and business requirements.

Why a Cloud Data Platform??

The modern enterprise is rapidly moving toward a hybrid IT environment where applications run in multiple locations across public, private, or community clouds. While many enterprises still rely on traditional monolithic databases, they increasingly use multi-cloud environments that include both public and private clouds. In addition, most large enterprises now leverage some form of analytics software to mine and analyze their data.

The growth of big data has created new challenges for enterprises. They need to store more data than ever, but they also face security concerns about protecting sensitive information from hackers and malicious insiders. To address these challenges, enterprises are turning to cloud data platforms to help them manage their data in the cloud, enabling you to add capacity when needed quickly. You can then query your data from any device at any time.

Cloud data platforms are designed to handle large volumes of data efficiently. They typically offer high performance and scalability and often come with built-in tools to help you automate processes and streamline operations. Some platforms also provide real-time analytics, which enables you to get answers to questions immediately. For example, you can set up alerts to know whenever there is a problem accessing your data.

Cloud data platforms also make it easier to share data among users. Instead of building custom interfaces and installing software, you can point your web browser to the platform’s interface.

This article will help you understand some key considerations as you evaluate data platforms. We’ll also discuss the pros and cons of each type of platform and give examples of how each could work for your organization.

What are some of the top modern cloud data platforms?

Data and analytics technical professionals are always looking to compare the top cloud data platforms:

• Microsoft Azure Synapse
• Snowflake Data Cloud?
• DataBricks
• Amazon Redshift
• Google BigQuery

Cloud Data Platform - Selection Framework

To help organizations make informed decisions, we use a technology selection framework that helps guide organizations through the process.?This framework includes three phases:?

Modern Cloud Data Platform - Use Cases:

When choosing a cloud data platform, organizations should consider three primary use cases:

• Data warehousing: for business intelligence (DWBI) reporting, analytics, and dashboards
• Data engineering: for Extract, Loading, and Transforming (ELT), data cleansing and preparation, and data integration.
• Advanced analytics:?including predictive modeling, machine learning, and deep learning

Modern Cloud Data Platform Requirements:

The second phase of our framework involves defining requirements. Organizations must identify their specific needs before making any decisions about data platforms. These include identifying the following requirements.

Each cloud data platform offers different capabilities, depending on its level of maturity. When evaluating a platform, consider the following:

• Data Volume: How much data do you plan to store? Are you storing structured data or unstructured text documents? Do you want to store images or videos? What kind of data do you intend to process?
• Analytics Capabilities: Which analytic functions do you need? Is your data stored in relational tables, JSON files, or other tables? Will you perform ad hoc queries or create complex reports?
• Security Requirements: How secure do you want your data to be? Do you require encryption? If so, which algorithms should you use?
• Cost: How much does it cost? Does the service charge per gigabyte or month?
• Platform Maturity Level: How mature is the technology behind the platform? Is the platform based on open-source technologies such as Apache Hadoop or proprietary solutions like one of the CSPs?
• Platform Features: What additional features does the platform provide? For example, does it support machine learning? Does it have an API?
• Performance: How fast is the platform? How scalable is it? How easily does it scale?

Business Case

One of the critical components we always include is a complete business case model that calculates the return on investment (ROI) that enterprises may realize by deploying cloud data platforms.

Years of experience working with enterprise architecture (EA), technical, and financial decision-makers revealed the following benefits that organizations can expect to achieve:

• Reduced costs:?Organizations can reduce their overall costs by 30% or more by migrating from on-premises data warehouses to the cloud. In addition, they can save on operational expenses, such as hardware and software maintenance, power and cooling, and staffing.
• Increased agility and speed:?Cloud data platforms can help organizations become more agile and responsive to changes in business conditions. They can also help teams iterate faster on analytics projects and get new applications and features to market more quickly.
• Improved performance:?Cloud data platforms can improve query performance by up to 10x compared with on-premises data warehouses. Furthermore, they can scale elastically to support concurrent users and enable real-time analytics.

Strategic Planning Assumptions

Legacy systems such as on-prem data warehouses are quickly hindering data-driven organizations. Enterprises must adopt a cloud-based data platform to keep up with their data needs and competitors. The following strategic planning assumptions underpin our forecast for the cloud data warehouse market:

• The global pandemic will accelerate the adoption of cloud data warehouses as organizations look to improve their agility and responsiveness to changes in business conditions.
• Cloud data warehouses will become a core enterprise architecture (EA) component as organizations shift to a cloud-first strategy.
• The market for cloud data warehouses will grow at a highly rapid rate into 2025.

Which Cloud Data Platform is Best?

Cloud data warehouses are purpose-built for cloud environments and offer many benefits over on-premises data warehouses. They are fully managed and scalable and support real-time analytics. In addition, they can be deployed quickly and easily.

?When choosing a cloud data warehouse, there are many factors to consider. Here are a few key considerations:

• Deployment model: Public, private, or hybrid?
• Pricing model: Pay as you go or subscription?
• Data types supported: Does the data warehouse support the data you need to store?
• Machine learning capabilities: Does the data warehouse provide built-in machine learning capabilities?

Your organization’s appropriate cloud data platform will depend on your specific needs and requirements. Be sure to assess your needs carefully before making a decision.

Also, you may have already noticed that the sales presentations of different technology vendors don’t always tell you everything about their products. As technology evolves, it’s essential to keep up with the latest trends. More importantly, stakeholders have different needs, so discussing with all stakeholders is crucial before choosing a modern cloud data platform.?

Proof of Concept (POC) / Pilot

Are some cloud data platforms cumbersome or perhaps unexpectedly easy to manage? The best way to discover the truth behind your top choices is to test vendors’ technologies independently. It also provides an excellent opportunity to feel how the technology works. In short, we recommend carrying out the following steps:

1. Define the most important and potentially complex use cases for your data platform
2. Run a small POC project to test these use cases by considering functionality, performance, and security aspects
3. Get the best available experts to help with the POC project. They can utilize their previous experience to discover potential issues with different technologies.

Discussing and agreeing on the potential solution with all relevant stakeholders is also critical. When company policies prevent selecting the best technology available, working on this inside the organization is worthwhile and aiming to change those policies with relevant stakeholders.

In Summary

Cloud data warehouses have become a core component of enterprise architecture as organizations shift to a cloud-first strategy. They offer many benefits over on-premises data warehouses, including improved performance, scalability, and real-time analytics.

Many factors exist when choosing a cloud data platform, such as the deployment model, pricing model, supported data types, and machine learning capabilities. All in all, there are a tremendous number of factors to consider. Your organization’s right cloud data warehouse will depend on your specific needs and requirements. Be sure to assess your needs carefully before deciding.

Proof of Concept (POC) / Pilot projects are a great way to test different vendors’ technologies independently. Discussing and agreeing on the potential solution with all relevant stakeholders is also critical. When company policies prevent selecting the best technology available, it is worthwhile to work on this internally and aim to change those policies with relevant stakeholders. Stay updated with the latest developments to ensure you make the best decision for your business.