Photo by John Adams / Unsplash
When it comes to innovation, leading companies throughout the world are openly communicating about it. Variables differ, but they all have an innovative culture, as well as agility and speed in common. The last two, in particular, are critical for any organization's ability to innovate. But where do you begin? We are fortunate to have new technologies, such as the cloud, that encourage innovation. In this article, we will look at how Microsoft Azure may help your organization innovate by using technologies, data, AI algorithms and machine learning.
Challenges in starting your data journey
Data has become a critical component of the decision-making process. But how can an organization become more data-driven, enabling it to be more agile and innovative? There is no way around the cloud as the foundation for a secure and governed data platform. We often see that businesses are frequently faced with a dilemma: whether to move fast or remain secure. The ability to do both is provided by establishing a cloud foundation.
Despite the fact that analytics and AI are the most important investments for company leaders, they face these challenges in becoming more data-driven:
- How to get the best return on investment;
- Cultural difficulties;
- How to become experienced data users;
- And how to get rid of data silos.
Read the Harvard Business Review Analytic Services report, Understanding Why Analytics Strategies Fall Short for Some, but Not Others.
Two critical analytics systems
Another challenge is that businesses are forced to maintain two critical, yet independent analytics systems: a data warehouse and a data lake. Every well-known company has a data warehouse with structured relational data. But do you want to experiment with big data and apply data science? Then a data lake is essential for exploring unstructured data and using algorithms to search for relationships. In Azure Synapse you find both a data warehouse and data lake to start your data journey.
What is Azure Synapse?
Azure Synapse, Microsoft’s PaaS (Platform as a Service) offering, integrates all your data (on-premises, cloud and streaming data) in one single environment.
In the platform you will find three unique components:
- Business-critical data and dashboards, supported by data warehousing;
- Data lakes to clean and explore (un)structured data;
- Power BI (seamless integration) to create interactive data representations.
If you are using Synapse and have a proper dataset, you can start using Azure machine learning. So, to make data-driven decisions, you do not have to make a lot of custom developments or use lots of different tools. It all comes together in Azure Synapse.
Advantages of data analytics in Azure
When you have that data-foundation on Microsoft Azure, you can start your data analytics. 85% of those who had already done so, agreed or strongly agreed that well-integrated analytics databases and storage, a data management stack and business intelligence tools, were beneficial to their organization. Furthermore, customer satisfaction increased by 60% and they experienced 27% faster time to insights by using data. Finally, data can support businesses in cutting costs by 26% (see this study).