Banking Data Lakehouse
A data lake is a data management solution built to harness the large volumes and variety of data, coming from many different data sources. This data needs to be collected and analysed to enable accurate data-driven business decisions at the minimum cost and complexity.
Data lake projects often fail to produce a return on investment because they are complex to implement, need specialized domain expertise and take months or even years to roll out. In most cases the data lake ends up not used efficiently and the value from the data is not realised.
Data lake projects often fail to produce a return on investment because they are complex to implement, need specialized domain expertise and take months or even years to roll out. In most cases the data lake ends up not used efficiently and the value from the data is not realised.
Turn data into insights and business outcomes
ConnectIQ Banking Data Lake is a next generation big data analytics platform, designed to meet big data challenges and provide a framework for data engineering, data science, analytics and machine learning.
It stores all your Temenos and Non-Temenos data, structured, semi-structured or unstructured, across your organization into a single consolidated data store, with banking data marts that support multi- dimensional reporting and analytics.
It stores all your Temenos and Non-Temenos data, structured, semi-structured or unstructured, across your organization into a single consolidated data store, with banking data marts that support multi- dimensional reporting and analytics.
Simple
Unify your data, analytics, and AI on one common platform for all data use cases
Open
Unify your data ecosystem with open source, standards and formats
Collaborative
Unify your data teams to collaborate across the entire data and AI workflow
Faster design, deployment, and data automation with zero coding
Optimised for the Cloud
ConnectIQ can be available both as an on-premise solution and on all three major clouds - Amazon Web Services (AWS), Microsoft Azure and Google Cloud.
Normalised Data Model
Built with normalized and dimensional modeling techniques, it extracts and self-updates metadata and production data from your applications, and creates a normalized database for faster search and querying.
Real-time data event streaming
It offers highly scalable, real-time data event streaming, enabling you to stream, transform and clean-up your data. The solution offers also scheduled data synchronization method.
Data Engineering
Data Engineering provides an intuitive drag-and-drop interface to integrate and process Temenos and Non-Temenos structured and unstructured data through automated deployable pipelines.
It simplifies ETL processes and data ingestion from a variety of sources - cloud or on-premise- without impacting the performance through a scriptless no-code approach. It can connect to different Databases like SQL, NoSQL, Cassandra, Oracle, etc as well as files like CSV.
Built-in, next gen ETL
It features a built-in ETL tool with Reconciliation framework for Data Migrations and Financial Reconciliation. It helps data engineering teams simplify ETL, by adding enterprise scalability, reusability, flexibility, high performance, and data governance, to the classic capabilities of ETL.
Continuous Data Integration
ConnectIQ has a data integration layer with pre-built integration with many sources to support continuous data integration between different systems, and can easily identify and extract/load only the changes – Delta’s.
AI & ML at the core
It uses AI and machine learning models offering higher quality data from multiple sources. This means that banks can make faster, more accurate and explainable decisions driven by AI & ML algorithms.
Operational Data Store
The data store holds all the diverse data, tables and query results. It offers a Data Portal with easily consumable Data Models with Fit-for- purpose operational core data. Users can run fast data searches and get access to the desired data in seconds
Self-service data preparation
Provides a secure portal for data consumers to interact and work with data and perform their own incremental transformation on the data as and when required.
Data Governance
Through automation, it simplifies and enables data governance and security, and keeps track of traceability of changes in your data with version control, helping to trace data throughout its lifecycle while ensuring regulatory compliance.
Data Archiving
Provides secure, role-based access for all the archived data in a central repository that contains both volatile and non-volatile data for ‘live’ and ‘read only’ purposes.
The benefits
Reduces data preparation
and data integration efforts up to
and data integration efforts up to
90%
Increased scalability,
flexibility and performance
flexibility and performance
Achieve the lowest TCO
and superior ROI
and superior ROI
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