How the Azure Technology Stack Comes Together to Enable Powerful Analytics on the Cloud

From staying up-to-date with market trends to mitigating risks and enhancing the customers' experience, data is the epicenter of business innovation. The formula to unlock the power of data is to leverage it seamlessly across all the stages of business, from collecting and extracting insights to delivering personalized user experiences. That's what data analytics and, more importantly, cloud analytics make possible. 

According to a recent analysis, the cloud analytics market is expected to grow to $65.4 billion by 2025, at a CAGR of 23%. But what does the cloud have to do with business data? Here's a deep dive into understanding businesses can use the power of data through effective cloud-based solutions. 

The Cloud and Data Analytics – The Powerful Connection 

More and more companies are gravitating towards the use of cloud-based approaches to digital transformation. And why shouldn't they, since the cloud offers scalability, cheaper rates compared to on-premise, and efficient use of resources, among others.  

While cloud drives these incredible changes to the business process, cloud analytics is a whole new ball game and is becoming a powerful enabler in the modern analytics space. With various handy analytical tools, cloud analytics uses businesses' cloud-stored/on-premise data to extract insightful information under different categories.  

That said, analytics on the cloud encompasses data security, optimum system performance, and faster data processing to affordability and use of advanced tech like ML/IoT. Major cloud providers today include Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP). Out of these, Azure provides an edge, thanks to its robust solutions and wide range of tools to support data analytics needs.  

This unmatched combination of data analytics and cloud computing in Azure is a key driver to many data-driven success stories. Read on to find out how Azure makes it all possible. 

How Is Azure Used for Data Analytics? 

If a business wishes to leverage data that can, in turn, cater to the growth, there's no better enterprise analytics solution than Azure's tech stack. Azure cloud services include Azure Data Lake, Azure Data Factory, Azure Synapse Analytics, Azure Analysis Services, Azure ML, Azure SQL DB, and Databricks. 

Let's briefly look into what the key components of the Azure technology stack  offer for enterprise analytics: 

Azure Data Factory 

• A data integration service is used to build pipelines that can move data from multiple sources, transform the data, and load it to the required destination with optimum security. 
• Data Factory is a preferred tool for organizations transitioning to the cloud, as it enables simple connection of their on-premise data sources. 

Azure Analysis Services 

• Analysis Services is used to build multiple data models on the cloud.
• Its modeling features can extract data from various sources and secure that data as a single tabular data model. 
• The singular view enables simpler viewing of data that's easy for businesses to understand and implement.

Azure Synapse Analytics 

• Synapse Analytics includes an integrated orchestration engine - Data Integration, that creates data pipelines and expedites data transformation. 
• It can process and manage large SQL tables with high-speed SQL query processing. 
• In addition, it provides powerful insights through the data and can be easily applied to machine learning models. 

Azure Databricks  

• Azure Databricks is an Apache Spark-based data engineering tool that helps simplify data science on larger workloads. 
• It provides a shared workspace that allows effective collaboration between data engineers, data scientists, and business analysts.  
• Databricks can enhance machine learning capabilities with its quick integration with Azure Machine Learning (Azure ML). 

Azure Data Lake 

• As the name suggests, the Azure Data Lake allows storing and processing of data of all shapes and sizes. With no compromise to speed.
• It works with internal IT systems and processes data on-demand or on a pay-per-job basis. 
• Further, it can develop and run parallel data transformations and processing programs in languages like R, Python, or .Net.

What It Takes to Move Analytics to the Cloud 

All the tools within Azure's tech stack, considered individually or in combination, serve many enterprise analytics or data warehousing use cases. With an in-depth analysis of the current pain points, challenges, and business goals, one can choose the right tool to fully benefit from the cloud advantage. 

But is it that simple? Here are some critical things to consider before moving analytics to the cloud: 

1. Do the analytics solutions benefit the business and data needs for the long term rather than being a quick fix? 
2. Do the strategies provide customers with much-needed agility, stability, and flexible systems? 
3. How does this transition fair when considering the transition speed, cost-effectiveness, and performance improvement opportunities? 
4. Does the business have a solid data management foundation since cloud analytics requires data consolidation from multiple sources - on-premise and/or in the cloud? 
5. Is there sufficient skilled talent? Moving analytics to the cloud requires a whole lot of advanced technological implementations, as in Microsoft Azure's services.  

Moving analytics to the cloud is not a "lift and shift" approach. It requires a thorough investigation, from where the business stands in the cloud game to the available resources and investments at stake. 

The Bottom Line 

If you're a company looking to streamline operations, maximize your data use, and reduce costs, then there's no better time than now to transition your analytics to the cloud. With the right skills and capabilities, you can transform your data into actionable insights while providing your customers with an optimum experience. 

At Novigo Solutions, we use Azure's powerful cloud technology and data analytics to position your company to excel in the market. We implement the right Azure tech stack by thoroughly investigating your data, business goals, and available resources. 

Drop us a line today to get started on your cloud data analytics journey.