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Self-Service Data Platform for Your Hyper-Distributed Data Needs

#cloud-migration #multicloud #computing-at-scale #modern-data-platform #data-on-cloud #data-integration

Mosaic Decisions, LTI’s modern data logistics platform, harnesses valuable data to generate actionable insights, which can facilitate business transformation and enhance the quality and speed of decision-making. Equipped with capabilities of data ingestion & integration, storage & governance, advance analytics, the platform decodes structured & unstructured data at enterprise speed and scale.

Data on Cloud

Simplifying and accelerating an organization’s journey onto Cloud (AWS, Azure, GCP) by utilizing pre-configured, ready-to-assemble platform kit for data and purpose-built, cloud-native ETLs for cloud warehouse technologies (Snowflake, BigQuery).

Accelerated Data Ops & Data Lake Setup

Enable setting up of Big Data Lake, using intuitive drag & drop features to connect & ingest, integrate & prepare, process & transform and manage & govern by tapping into varied formats of hyper-distributed silo-ed data and reduce time to harness enriched analysable data.

Streaming Data Analysis

Capture, store and process data-in-motion, as well as data-at-rest, to enable real-time & batch analytics and insights generation.

Optimized Cost Investment

Multi-cloud support enables no cloud-vendor lock-in and optimizes and controls IT spend by enabling optimized data processing and technology abstracted self-served features reduces skilled resource investment.

Enterprise Governance & Security

Integrate with enterprise authentication & authorization to better govern and manage the workloads and lineage to demystify data to decisions journey with an effective, collaborative and centralized platform management & controls.

Enterprise Data & Analytics Hub

Integrated data-science workbench enabled with rapid feature engineering capabilities and flexibility to create and access data APIs for external analytical consumption.

Product Features

Data Connectivity & Ingestion

Connect to internal & external data sources and preserve source metadata information.

  • Extensive pre-built data connectors library for - RDBMS, file systems, cloud storages, NoSQL, streams and advance connectors for external applications.
  • Connect, process and ingest structured, semi-structured and unstructured data formats.
  • Readily available data profiling & data quality dashboard.
  • Manage, maintain and discover source metadata and share data assets based on roles and permissions.
  • Centrally curate, manage and organize enterprise data assets
  • Smart data type validation and correction during ingestion process.

Data Orchestration & Processing

Easy-to-use, self-served intuitive drag & drop features for data orchestration and processing.

  • No Code – Low Code features enables faster design & development.
  • Batch and real-time data processing enable accelerated analytics & insight.
  • Ever-evolving prebuilt function library to build complex business rules for data validations.
  • Workflows to manage and build complex business transformation and error-handling scenarios.
  • Runtime column propagation to address code reusability.
  • Extensibility to execute custom codes.
  • Workflow checkpoints allows for recoverability of data pipelines from point of failure.
  • Agnostic to data storage layer

Runtime Execution and Integration

Multiple runtime environment support and microservice-based platform architecture provides flexibility to plug-and-play.

  • Platform-native runtime execution support for Spark.
  • Cloud-native pushdown ETLs optimized for Snowflake and BigQuery.
  • Integrated data science workbench to operationalize data science activities.
  • Communicates using RESTful web services to provide standardized way of interoperability of information in JSON format with other application using https protocols.
  • Multiple SDKs for defining custom functions.
  • Interoperability with applications ensured using https protocols, and communication using RESTful web services.
  • Integration with GIT repository for code version control.

Scalability & Availability

Serverless platform architecture to execute workloads on any infrastructure.

  • Serverless platform architecture.
  • Deployable on-cloud and on-premise.
  • Multi-cloud support for spark-based workloads to run anytime anywhere.
  • Cloud PaaS adoption caters high availability of the platform.
  • Kubernetes adoption enables high scalability for workloads.

Collaboration & Change Management

Collaborate, share and manage data operations across enterprise-wide data community.

  • Collaborative environment for data engineering teams to manage, share and control.
  • Centralized metadata management.
  • Share, authorize and control the access of data assets and pipelines across data engineering teams.
  • Manage workload resource configuration for optimal infrastructure utilization.
  • Configure cloud data warehouses to manage utilizations for application specific cloud-native transformations.
  • Lineage to map data transformation path from source to target.

Governance & Security

Integrate with enterprise governance and security measures and standards.

  • Centralized user management service to manage users, roles and actions on the platform.
  • Integrate with enterprise single sign-on (SSO), LDAP or AD.
  • Centrally curate, manage and organize enterprise metadata data.
  • Centralized scheduling and logging mechanism to monitor cluster workload execution.
  • Alerts, notification and grant access management and mechanism.
  • Audit control checks and reports to keep a tap at user activities on the platform.
  • Versioning to manage and control code migration.

Resources

Mosaic Decisions

Simplified Data-to-Decisions platform for accelerated business outcomes @Speed and @Scale

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