Title of the page: Quickly migrate and manage data science, data warehousing and complex data processing workloads on Microsoft Azure
ADA ON AZURE
ADA helps enterprises run a wide range of data and analytic workloads on Microsoft Azure. ADA’s end-to-end services bundle Azure infrastructure with best of breed and open source databases, analytics engines, security, management and operations. ADA delivers all capabilities in a simple “self-serve” interface, with a single fee that includes everything. ADA also includes software that makes enterprise data migration to the cloud secure and simple, even from datacenters or complex environments. Enterprises radically simplify cloud data processing with ADA on Azure, driving faster outcomes in a fraction of the time.
- Accelerate cloud deployments and run a wide range of data and analytics processing on Microsoft Azure, including Data Science, Data Warehouses, Data Marts or other projects.
- Supercharge analytics and data science with the latest technologies, simplified and optimized to work with your tools and methods. (R, Python, SQL, Spark,…)
- Easily migrate and manage workloads from Cloudera, Pivotal Greenplum, IBM Netezza and others. Single-tenant, secure, end-to-end monitoring and logging.
- Includes built-in data movers, which make it easier to get data from SaaS apps, cloud sources and enterprise data systems.
- Maintenance free “as a service” operations, including 24 x 7 monitoring, patching, backup & restore and upgrades.
ADA’s flexible Data Science Sandbox as a Service on Azure helps teams use the cloud for a wide range of analytics including R, R Studio Server Pro, Python, SQL and more, running on optimized, high-performance cloud infrastructure. ADA’s flexible sandbox as a service helps data science teams use the cloud for a wide range of analytics including R, R Studio Server Pro, Python, SQL and more, running on optimized, high-performance cloud infrastructure.
- Run analytics at cloud-scale without having to manage or maintain the underlying technology platform. Includes embedded analytics engines for high-performance processing and iteration. Typically powered by Apache Spark and Hadoop technologies from Cloudera and others, all managed and optimized by ADA’s expert team.
- Easily collect, move and store big data from numerous cloud and on-premises sources, including SaaS, purchased data, public/open data, IoT, social, etc.
- Migrate on-premises Cloudera Hadoop/Spark workloads to Azure to accelerate results, minimize administration requirements and reduce unnecessary costs.
- Stay focused with an unconstrained analytic platform that is optimized and fully supported “as a service,” including security, patching, upgrades, backup/restore, etc.
Run analytics, business intelligence and data warehousing workloads in the cloud, with an optimized service that works with your existing tools and is powered by MPP SQL data processing. Use data marts to share data with partners, customers and contractors.
- Get data marts or warehouses that work with any standard SQL business intelligence, visualization or advanced analytics tools including Tableau, Spotfire, etc.
- Migrate data warehousing workloads to the cloud, offload appliances, free capacity in on-premises appliances such as IBM Netezza, Actian Matrix, Pivotal Greenplum and others.
- Collect and consolidate data from a wide variety of SaaS, cloud and on-premises data sources; Improve data access for employees, partners, customers, contractors, etc.
- Get plug and play integration with existing ETL, data warehouse appliances, analytics and business intelligence tools – augment current processes easily.
HOW IT WORKS
Each ADA customer has its own secure, single-tenant environment on Microsoft Azure. Within that environment, companies may have multiple databases for different workloads or users. Companies connect to data sources via the ADA Gateway, which encrypts and moves datasets to Azure from cloud or on-premises sources. Software deployment, provisioning and ongoing management are all included as part of the service fee. Users connect to data in ADA with their preferred analytics tools or methods — or by using the ADA web interface, scripts and APIs.
Companies may have multiple data engines which are all intelligently provisioned, integrated and managed “as a service” by ADA. Data Mart as a Service typically supports analytics and business intelligence applications. Data Science Sandbox environments are often optimized for larger datasets and include Hadoop, Spark, R, Python and many other components.
All functions are packaged and delivered as a single service. Enterprises pay an annual subscription, with pre-negotiated expansion tiers for predictable budgeting and planning. Scale as your data grows, with an enterprise service that ensures no surprises.
“We’re 6 to 8 months further ahead by having ADA. Our data science team wants to spend their time adding value, rather than doing the housekeeping work. The primary benefit is speed. Now the team has a structured place to share their data, work and ideas.”