Data Integration and Automation
From improving the speed of your cloud capabilities to providing real time data analysis capabilities, SME offers solutions to your biggest data integration and automation problems.
From improving the speed of your cloud capabilities to providing real time data analysis capabilities, SME offers solutions to your biggest data integration and automation problems.
From heterogeneous sources that include production databases, data warehouses, SAP, and mainframe systems, to flat files and SaaS applications, we deliver to all major target platforms, then refine it for analytics. Below you can see the three data delivery options our solutions provide.
We can replicate committed transactional data, either in bulk or via real-time change data capture (CDC), to relational databases, ranging from Oracle to SQL Server to PostgreSQL, on premises or in the cloud. We also can replicate to or from flat files. This enables use cases such as migrations, reporting and analytics.
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We deliver the transactional data streams to modern data warehouses such as Snowflake and Azure SQL DW, using automated data delivery and modelling methods to enable your reporting and analytics activities. We automate model creation, data warehouse creation, data mart creation, table creation, data instantiation and source/target mappings. You can manage all these tasks as an integrated workflow.
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We take relational transaction streams and stitch them together into a common format that can be readily consumed for analytics on Big Data platforms such as Amazon EMR, Azure HDInsight and Google Dataproc. Our solution automatically creates, loads and updates data stores, and accelerates dataset readiness for analytics. You can then process the datasets we refine alongside non-relational and unstructured data from other sources.
Read Our Case StudyData management comprises four individual segments: data integration, data quality, database management systems and master data management.
Data integration includes practices, architectural techniques and tools that enable organizations to ingest, transform and combine data. This data is then delivered to users throughout the organization for a variety of use cases, including data governance and management, application data management and the synchronization of data between operational applications.
Use Cases for Data Integration
Improving data management efficiency.
Meeting performance, capacity, and uptime requirements.
Aligning data, infrastructure, and business requirements.
Organizations are modernizing their data architectures in three ways:
Data management comprises four individual segments: data integration, data quality, database management systems and master data management.
Data integration includes practices, architectural techniques and tools that enable organizations to ingest, transform and combine data. This data is then delivered to users throughout the organization for a variety of use cases, including data governance and management, application data management and the synchronization of data between operational applications.
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Do you have a tough time understanding the lineage of your data?
Learn where your data comes from with a brief explanation of data lineage from SME.
Is your data refreshing in real time and automated?
Learn about our real-time visual analysis without the need for code or lost productivity
Are you looking to upgrade from your legacy system?
More and more businesses are identifying the need to upgrade from their legacy systems. Find out what that transition looked like for one of our clients.
Finding the right Data Storage and Processing solution can result in better flexibility in scaling and workload management, better control of the cost of storage and computing, and a better source of your data that allows for real-time analysis and reporting. Learn how SME consults on finding the right strategies, objectives and activities to fulfill your strategic plan.
Learn MoreWithout Data Governance and Literacy, the insights that are hidden in your data become limited. SME Solutions Group works to build data-driven cultures by implementing our Data Governance and Literacy solutions. We choose to work with partners that provide data glossaries, data catalogs, and other data management systems that help uncover the true insights in your data.
Learn MoreMake data a key business asset. SME consults by assessing your current business landscape, data ecosystem, and business processes and guiding you through recommendations. We offer Data Analytics and Science solutions that allow you to ask relevant and contextual questions without the reliance of IT, because we believe that every business should have a goal to become data-driven.
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Matillion is an ETL software that allows you to build a robust data pipelines to cloud data warehouses.
Matillion's extensive list of pre-built data source connectors allows for easy integration, and flexible pricing allows for a cost-efficient pay-as-you-go plan.
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StreamSets is a data operations platform, consisting of a collection of programs designed to control changes in data, data sources, data infrastructure, and data processing.
SME partners with StreamSets because of its ability to quickly ingest, transform and move data while helping you adopt the latest innovations.
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Precog, the world's first AI Data Loader, allows you to connect to all your data sources, whether it be a data warehouse, database, or data lake.
SME and Precog have partnered to provide a SaaS based MSP offering called SME Data Movement Services, where we manage it completely.
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