Accelerating Digital Transformation with Data & AI

According to the World Economic Forum, Artificial Intelligence (AI) is expected to turn into an essential business driver across several industries. As an example, 77% of business leaders from Financial Services Institutions are anticipating that AI will have a high or very high overall importance to their businesses within two years and they are increasing the adoption of AI across key business functions.

To be able to transform our organizations, AI needs to be driven at the highest levels of the company - at the CEO level and her/his board of directors. In my experience, we should prioritize key drivers such as:

• AI Ethics Enshrined. The organization should clearly state the ethics of how AI will and will not be used. How they will maintain privacy and security of data. This is crucial to build on the trust relationship with our employees, partners and end-customers.
• Focus on Customer. As this transformation journey unfolds, as employees, we should focus less on lower value tasks and focus more on customer experience and relationships.
• Data Acquistion will be a new skill that will need to be built out (or leverage free/buy external data sets) to be able to consume them across the business so, everyone can get value.
• AI Capability Development. Lastly the development of an AI capability should be a priority key – there is a war for talent and Microsoft can provide you with help across all of these areas. 

Becoming “Data-driven” 

It is proven that data-driven organizations are 23 times more likely to acquire customers, 6 times as likely to retain customers, and 19 times as likely to be profitable as a result. That is why, becoming data-driven has become a priority for industries like Banking, Insurance, Manufacturing, and Energy (including Mining and Oil & Gas).

But what this means for an organization:

• Foster a culture of data-driven decisions at all levels within the organization
• Explore data sources which go beyond the batch analysis of transactional data and infuse a variety of internal and external data sources and real-time data ingestion
• Break down data silos that exist within the organization
• Encourage data stewardship from people within the organization 
• Focus on quality of data rather than just capturing data
• Align the business strategy to the data strategy
• Drive the business transformation with data

I want to encorauge you to read my previous articles: Data-driven Cultural Transformation to shape the New Normal and Building Intelligence Driven Organization (IDO). Let me know your opinion as a comment :) [smiling face]

Data Estate Modernization 

Establishing a modern data estate is a foundational step toward digital transformation. A data estate refers to all the data an organization owns, regardless of where it is stored.

The current massive growth in data and the increasing need for everyone to get immediate insights to demand a fast and highly-scalable data platform. When cloud, data, and AI work together, they offer new and exceptional opportunities for people and organizations to gain important insights to fuel innovation and growth of the business.

Organizations are demanding Data Estate Modernization related services to face challenges due to their legacy data environments and get value from their data. Besides the explosion in data volumes and the variety of data, the challenge is how to do it with velocity and the overarching security and compliance requirements.

Microsoft solutions can help migrate servers, databases, and applications to modern platforms on-premises or to Azure. As data types, volumes, applications, and architectures change, you can modernize your data with Azure Data Services.

A good way to start is engaging with Microsoft Consulting Services (MCS) to conduct a free two-day Strategic Cloud Adoption Envisioning Workshop. Strategic Cloud Adoption (SCA) provides a personalized and programmatic approach to accelerate your cloud adoption journey and help you to achieve your business goals. Based on an understanding of your unique business needs, we will help you by developing a modernization roadmap to enable a solid foundation for your digital transformation.

MCS can help you to build your cloud journey based on our experiences, approach, and solutions, together with your environment, requirements, dependencies, and maturity. We also consider other important factors such as your specific market, ecosystem, and industry.

Reasons to partner with Microsoft to accelerate your transformation with Data & AI

At Microsoft, we provide an integrated cloud approach that creates an unmatched platform for digital transformation. Our focus is on addressing the real-world needs of customers with Microsoft 365, Dynamics 365, and Azure integrating seamlessly to unlock business value for every organization from large enterprises to family-run businesses. Something I love is having Azure as our backbone and providing all the cloud computing services that your organization needs.

Microsoft provides an integrated cloud approach that creates an unmatched platform for digital transformation.

It doesn't matter which cloud technology you are using, you can count on Microsoft because we run on trust. As you know, trust begins with that commitment to shared success and prosperity, but it also extends to encompass your confidence in our technology and our ability to ensure privacy, cybersecurity, and responsible AI.

Today, I want to go deeper into three key reasons to help you choose Microsoft for your Data & AI platform and to build your digital feedback loop. 

1. Multi-Cloud, Hybrid, and Open
2. Responsible AI
3. Close your skills gap 

Multi-Cloud, Hybrid, and Open

Wherever the data is, Microsoft Azure can help you to unlock its potential. Build intelligent apps faster using the tools and technologies of your choice and AI that’s already built-in.

Azure supports a range of deployment options, popular stacks and languages, and a comprehensive set of data engines. You now can bring Azure Data Services (ADS) to on-premises, multi-cloud, and edge with Azure Arc.

I usually refer to Azure Arc as a set of technologies that extends Azure management and enables Azure services (including ADS) to run any infrastructure (on-premises, multi-cloud, and edge). In fact, you can now manage virtual machines, Kubernetes clusters, and databases as if they are running in Azure.

Today, Azure Arc allows you to manage the following resource types hosted outside of Azure:

• Servers - both physical and virtual machines running Windows or Linux.
• Kubernetes clusters - supporting multiple Kubernetes distributions.
• Azure Data Services - Azure SQL Database and PostgreSQL Hyperscale services.

Speaking of data-related services, Azure Synapse Analytics is a fantastic technology for converging data lakes and warehouses and to reduce the gap between AI and Business Intelligence (BI). Azure Synapse gives us the freedom to query data on our terms, using either serverless on-demand or provisioned resources at scale. In my perspective, brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

You should know that we had extended our Platform-as-a-Service (PaaS) offerings to support Open Source Databases and meet you where your organization is. Now, you can choose the database technology from a large catalog including Azure SQL Database, Azure Database for MySQL, PostgreSQL or MariaDB. How to choose will depend on things such as:

• Your application’s needs & technologies provided by your database strategy
• The skillset of the developers available
• Total Cost of Ownership

Why Open Source Databases in Azure? Besides our learnings working on database products for enterprise customers (i.e., SQL Server was released in 1989) and the cost to achieve scale, achieving high-availability (HA) with IaaS or on-prem installations require replicas as well as orchestration logic to handle the failure of a master (or the addition of expensive 3rd party solutions). With Azure Database Services, HA is built-in and orchestrated by the Azure Database Management Service which means there is no configuration by the customer necessary. Also, there are no replicas to maintain with Azure Database Services meaning no cost for your organization! Cool, right?

Last and not least, “Secure by default” is the standard for any Azure service, meaning elements such as SSL encryption between the database and application are turned on by default. Additionally, all data-at-rest is encrypted by default in Azure storage using AES 256-bit encryption. And since Azure Database Services are using OSS database engines, the Azure IP Advantage means that customers do not have to worry about litigation using an OSS product in Azure. Microsoft provides indemnification for any OSS first-party workload in Azure.

In conclusion, Microsoft provides a common service fabric across the Azure relational databases platform to allow you to build and deploy modern cloud-native apps. These apps can also leverage advanced services such as PowerBi, Azure Machine Learning (ML), Azure Cognitive Services, etc.

Responsible AI

At Microsoft we are committed to the advancement of AI driven by ethical principles that put people first. Therefore, we operationalize Responsible AI across Microsoft through a significant effort led by Microsoft's AI, Ethics, and Effects in Engineering and Research (AETHER) Committee and its working groups and our Office of Responsible AI (ORA). Together, Aether and ORA work closely with our responsible AI advocates and teams to uphold Microsoft responsible AI principles in their day-to-day work.

ORA is responsible for helping Microsoft put its principles into practice, both within Microsoft and through tools and practices that empower our customers and partners to do the same. The Office also helps to shape new laws, norms, and standards to advance responsible AI for society's benefit at large. You can learn more about our approach here.

As we did with the General Data Protection Regulation (GDPR), we are taking our learnings, patterns, practices, and tools to help you to turn Responsible AI into action in your organization.  

In my article AI Technology: Responsible Innovation with Positive Impact, you can learn more about Microsoft principles for Responsable AI and our ethics framework. If needed, we also can help you to define your own Responsable AI approach.

Close your skills gap 

Whether you're just starting or an experienced professional, Microsoft Learn can help you achieve your goals faster, with more confidence, and at your own pace.

Microsoft Learn is a completely free, online training platform that provides interactive learning for Microsoft products and more. Something that I love is the role-based training and learning paths for developers, solution architects, data scientists, AI engineers, and administrators (including Database administrators). In a single platform, you can learn about Azure, Microsoft Power BI, PowerApps, Dynamics365, Microsoft365, Office, and Visual Studio.

Learning paths are collections of modules that are organized around specific roles. As an example, an organization, team, and individual may plan their training based on the personas (*) participating across all parts of the Data Supply Chain: 

Data Ingest and Store

• Data Engineer Learning Path

Data Preparation and Train

• Citizen Data Scientist Learning Path
• Data Scientist Learning Path

Visualize

• Business Analyst Learning Track
• Business Decision Maker using the Industry Track (based on Microsoft AI Business School): Financial Services, Manufacturing, HealthCare, Education, Goverment, etc.

(*) The concept of "Persona" in design thinking represents a typical user who is the target audience of the solution. Usually, include a high-level description, their needs, their thoughts, goals, and available tools (including technology).