In partnership with: Microsoft Azure

Unleash intelligent disruption with a modern data warehouse

Accelerate data warehouse modernization with advanced data management for Microsoft Azure

Data is the foundation for all digital transformations. It powers businesses to disrupt markets

and expose new revenue streams. As businesses journey deeper into the cloud, those that can

scale, adapt investments to meet new needs, and connect on-premises, cloud, and hybrid data

across platforms and business functions will emerge as winners.

Enterprise data typically resides across multiple internal and external sources, in structured

and unstructured forms. Key business stakeholders need access to it to make impactful

business decisions based on relevant insights.

Moving data workloads to cloud platforms, such as Microsoft Azure, provides the performance

and agility needed with the added economies of cloud infrastructure. More people can have

greater access to data to help them make decisions faster and with greater confidence,

accelerating innovation and beating competitors to market with new opportunities.

Common data management challenges and recommendations

Challenge

More data from more sources = more complexityBusinesses consume data from more sources than ever before: big data, Internet of Things

devices, business applications, and social media feeds—residing on-premises, in the cloud,

or elsewhere. Monitoring and managing data in production is key to catching and correcting

problems before they escalate out of control. The increased variety of data sources makes this

task more complex.

Recommendation

Simplify with intelligent data management Modernize your data architecture with intelligent data management purpose-built for Microsoft

Azure that easily adapts and scales as your data types, volume, and applications change.

Challenge

Costs and complexity of on-premises workloadsWhile IT organizations shoulder the high overhead and complexity of on-premises systems, at the

same time meeting intensifying business demands with new technology and maintaining legacy

infrastructure, they often ask, “Why are we doing this to ourselves?”

Recommendation

Migrate data workloads easily to Microsoft Azure Reduce your on-premises footprint, decrease costs, and increase agility by moving existing

workloads, applications, and datacenters to Microsoft Azure. Leverage tools that provide insight

into your enterprise-wide data to preserve lineage and then help identify and automate the secure

migration of a wide variety of hybrid data workloads.

Customer story

Life Time Fitness, a health and lifestyle company, built an efficient, cost-effective,

cloud-based architecture for data warehousing and accessing data. With the

ability to efficiently bring a wide variety of data into Microsoft Azure—from cloud

applications like Workday to on-premises applications, including point-of-sale

systems—Life Time could better understand its members’ behaviors and offer

the right programs and services to help them meet their fitness goals.

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Challenge

Limited agility and scalability of traditional data warehousesTraditional, on-premises data warehouses have limited capacity and are costly to support. Most

organizations, particularly medium- to large-size ones, still have a substantial existing investment

in on-premises computing infrastructure, processes, and support. There can be good reasons for

this, as some highly specialized and complex systems don’t fit the cloud model. These systems

are expected to be maintained and supported for years to come.

Recommendation

Modernize by moving to the cloudWhen businesses use a flexible, scalable cloud data-warehouse, like Microsoft Azure SQL Data

Warehouse, capacity and cost concerns are dramatically alleviated. You don’t want to lose value

from your existing enterprise data warehouse or on-premises data integration solutions. With

hybrid data-warehousing environments, businesses keep the data and applications they want

on-premises and move the rest to the cloud for improved agility and lower costs.

To get the most benefit from a hybrid data warehouse, leverage versatile data integration

solutions to migrate and load the data into your new Azure data warehouse. Then, deploy

a unified and modular data management platform to manage your data through

subsequent updates.

Informatica: helping you unleash the disruptive power of data

Informatica Intelligent Data Platform™, a modern, modular, microservice-based platform,

accelerates data-driven digital transformation, enabling companies to unleash the power of data

to fuel innovation, become more agile, and realize new growth opportunities, resulting in intelligent

market disruptions.

The solution’s data management competency and prebuilt integration accelerate integrating,

managing, and migrating a wide variety of hybrid data workloads to Azure Data Services (SQL

Data Warehouse, SQL Database, Data Lake Store, Blob storage, etc.) from cloud and on-premises

applications, relational databases, and data warehouses.

Informatica’s machine-learning-based discovery engine collects data assets across the enterprise

through a graph-based intelligent data catalog, providing insight into your enterprise-wide data

prior to migrations. That way you can map out a predictable, viable, and manageable data

migration road map that preserves data lineage.

You can conduct analysis and testing of cloud-bursting capabilities to prepare for workload

spikes. This enables a more consistent, data-centric approach, promoting increased productivity

and reuse across these platforms.

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© Copyright Informatica LLC 2017. Informatica and the Informatica logo (and any other trademarks appearing in the document) are trademarks or registered trademarks of Informatica LLC in the United States and other countries.

Make possible what never existed before

Having the user-friendly, modern, and modular Intelligent Data Platform™ is a proven success

factor for agile analytics initiatives in a cloud or hybrid environment. Leveraging the right data

management platform means it can be reused for future use cases and projects, will future-proof

your analytics environment against changes, and will ease ongoing maintenance operations while

reducing manual workload.

To learn more, visit informatica.com/microsoft.

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