To undertake a digital transformation initiative, organizations are often asked to select a preferred modern data strategy or patterns – often defined as a data hub, data warehouse or data lake.
The choice is not as daunting as it might first appear. First, the way an organization wants to use its data, today and in the future, will help determine the best architecture. Secondly, but not less importantly, it’s not an either/or proposition – the best solution for many organizations will be an approach that encompasses more than one modern data strategy.
Data Rocket™ has worked for a variety of organizations – from enterprise banks to higher education institutions – because it takes a best of breed approach. To understand how Data Rocket supports modern data strategies, it’s important to define the key characteristics of each.
Data Rocket™ is an acceleration architecture that modernizes data infrastructure and delivers critical business insights – securely and accessibly. Data Rocket puts industry-best data technology in the hands of businesses of any size, unlocking dynamic ingestion, data mastering and 3rd party data integration.
Built with Talend’s Data Fabric and the Snowflake Data Cloud, Data Rocket spurs adoption through IP, integrations and blueprints. Data Rocket connects data to custom dashboards in PowerBI or Tableau, putting visual analytics and real-time reporting in the hands of decision-makers throughout an organization and supporting ML and AI applications.
With releases at least twice a year, Data Rocket builds accelerators and frameworks to respond to business needs and use cases. At its core, Data Rocket’s accelerated data architecture blueprint enables a modular ecosystem that supports the best components of each modern data strategy.
Data Rocket’s Enterprise Blueprints centralize data from disparate source systems into the Snowflake Data Cloud – in that way, it supports Data Hub, Data Warehouse and Data Lake models.
With automated, governed ingestion, Data Rocket further calls on the Data Hub model, ensuring that Data Governance is present throughout the data life cycle and supporting a mature Data Cloud environment where data can be immediately used and trusted – a primary component of Data Hub strategy.
The Audit and Control Framework features an out-of-the-box dashboard with views of historic and realtime data ingestion information. Data Stewards can perform targeted troubleshooting to identify and remedy suspect data at the source. Built-in data versioning provides data stewards the ability to go back in time to any point in the data history to pinpoint data inaccuracies. With a focus on high-quality data for operational use, analytics and reporting, Data Rocket supports Data Hub and optimized Data Warehouse strategies.
Data Hubs are considered bi-directional – just as a train travels to and from stations as it picks up and delivers passengers, so data is taken from and delivered to source systems. Data Rocket’s Mastered Data Accelerator is not bi-directional – it does not automatically update cleansed data within a source system. It does provide an affordable, built in Data Mastering Framework, creating a “Golden Record” for one version of the truth throughout organization.
The AI/ML Framework productionizes execution of AI/ML models within the Snowflake Data Cloud. While not bidirectional, the Framework provides a feedback loop between the operational database and data science applications, so users throughout the organization can easily access data science models. In that way, Data Rocket is more akin to a Data Hub than a Data Warehouse, where data science applications are performed outside the central repository and are not productionized.
Predefined views link datasets from Snowflake’s Data Marketplace to trusted internal data, unlocking high value insights to business line users, from the C-Suite, to product development, to sales and marketing. The 3rd Party Data Accelerator turns the Snowflake Data Cloud into the operational center for all business processes and users – a primary characteristic of Data Hub strategy. The Data Marketplace Accelerator is a critical component of Data Rocket for Financial Services, which provides predefined integration with Equifax and Segmint data solutions.
Data Rocket’s newest component, Data Quality Watch, is a governance tool providing automated profiling, with out of the box data stats and anomalies detection capabilities. Data governance is a central pillar of both Data Hub and Data Warehouse strategies. With Data Governance strategies taking place at the source system (Dynamic Ingestion) and with Data Quality Watch within the Snowflake Data Cloud, Data Rocket aligns most closely with Data Hub strategy.
Data Rocket is a comprehensive modern data platform that allows organizations to move from data to action. Data Rocket’s modular architecture allows Passerelle engineers to customize the platform to deliver value, based on an organization’s business needs and goals. Ready to get started? Contact us today.