Mozart Data Description
Mozart Data is the all-in-one modern data platform for consolidating, organizing, and analyzing your data. Set up a modern data stack in an hour, without any engineering. Start getting more out of your data and making data-driven decisions today.
Mozart Data Alternatives
IRI Voracity
IRI Voracity is an end-to-end software platform for fast, affordable, and ergonomic data lifecycle management. Voracity speeds, consolidates, and often combines the key activities of data discovery, integration, migration, governance, and analytics in a single pane of glass, built on Eclipse™.
Through its revolutionary convergence of capability and its wide range of job design and runtime options, Voracity bends the multi-tool cost, difficulty, and risk curves away from megavendor ETL packages, disjointed Apache projects, and specialized software. Voracity uniquely delivers the ability to perform data:
* profiling and classification
* searching and risk-scoring
* integration and federation
* migration and replication
* cleansing and enrichment
* validation and unification
* masking and encryption
* reporting and wrangling
* subsetting and testing
Voracity runs on-premise, or in the cloud, on physical or virtual machines, and its runtimes can also be containerized or called from real-time applications or batch jobs.
Learn more
Domo
Domo puts data to work for everyone so they can multiply their impact on the business. Underpinned by a secure data foundation, our cloud-native data experience platform makes data visible and actionable with user-friendly dashboards and apps. Domo helps companies optimize critical business processes at scale and in record time to spark bold curiosity that powers exponential business results.
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DataBuck
Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.
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Improvado
Improvado, an ETL solution, facilitates data pipeline automation for marketing departments without any technical skills. This platform supports marketers in making data-driven, informed decisions. It provides a comprehensive solution for integrating marketing data across an organization.
Improvado extracts data form a marketing data source, normalizes it and seamlessly loads it into a marketing dashboard. It currently has over 200 pre-built connectors. On request, the Improvado team will create new connectors for clients.
Improvado allows marketers to consolidate all their marketing data in one place, gain better insight into their performance across channels, analyze attribution models, and obtain accurate ROMI data.
Companies such as Asus, BayCare and Monster Energy use Improvado to mark their markes.
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Pricing
Free Trial:
Yes
Integrations
Company Details
Company:
Mozart Data
Year Founded:
2020
Headquarters:
United States
Website:
www.mozartdata.com
Media
Connect all your data sources with over 300 out-of-the-box connectors
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Product Details
Platforms
SaaS
Type of Training
Documentation
Live Online
Videos
Customer Support
Phone Support
Online
Mozart Data Features and Options
Data Extraction Software
Disparate Data Collection
Document Extraction
Email Address Extraction
IP Address Extraction
Image Extraction
Phone Number Extraction
Pricing Extraction
Web Data Extraction
Data Management Software
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Data Warehouse Software
Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge
ETL Software
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control
Data Preparation Software
Collaboration Tools
Data Access
Data Blending
Data Cleansing
Data Governance
Data Mashup
Data Modeling
Data Transformation
Machine Learning
Visual User Interface
Data Governance Software
Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management
Big Data Software
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Analysis Software
Data Discovery
Data Visualization
High Volume Processing
Predictive Analytics
Regression Analysis
Sentiment Analysis
Statistical Modeling
Text Analytics
Data Quality Software
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
Data Discovery Software
Contextual Search
Data Classification
Data Matching
False Positives Reduction
Self Service Data Preparation
Sensitive Data Identification
Visual Analytics
Mozart Data Lists
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