Learn More

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 6 Ratings

Description

AtScale streamlines and speeds up business intelligence processes, leading to quicker insights, improved decision-making, and enhanced returns on your cloud analytics investments. It removes the need for tedious data engineering tasks, such as gathering, maintaining, and preparing data for analysis. By centralizing business definitions, AtScale ensures that KPI reporting remains consistent across various BI tools. The platform not only accelerates the time it takes to gain insights from data but also optimizes the management of cloud computing expenses. Additionally, it allows organizations to utilize their existing data security protocols for analytics, regardless of where the data is stored. AtScale’s Insights workbooks and models enable users to conduct Cloud OLAP multidimensional analysis on datasets sourced from numerous providers without the requirement for data preparation or engineering. With user-friendly built-in dimensions and measures, businesses can swiftly extract valuable insights that inform their strategic decisions, enhancing their overall operational efficiency. This capability empowers teams to focus on analysis rather than data handling, leading to sustained growth and innovation.

Description

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.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Amazon Web Services (AWS)
Cloudera
AWS Glue
Amazon S3
Apache Airflow
Azure Cosmos DB
Azure SQL Database
Databricks
Google Cloud BigQuery
Google Cloud Dataflow
Google Cloud Platform
Microsoft Azure
Microsoft Power Query
PostgreSQL
SQL Server
Skott
Snowflake
Tableau
Teradata VantageCloud
jethro

Integrations

Amazon Web Services (AWS)
Cloudera
AWS Glue
Amazon S3
Apache Airflow
Azure Cosmos DB
Azure SQL Database
Databricks
Google Cloud BigQuery
Google Cloud Dataflow
Google Cloud Platform
Microsoft Azure
Microsoft Power Query
PostgreSQL
SQL Server
Skott
Snowflake
Tableau
Teradata VantageCloud
jethro

Pricing Details

No price information available.
Free Trial
Free Version

Pricing Details

No price information available.
Free Trial
Free Version

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Deployment

Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Customer Support

Business Hours
Live Rep (24/7)
Online Support

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Types of Training

Training Docs
Webinars
Live Training (Online)
In Person

Vendor Details

Company Name

AtScale

Founded

2013

Country

United States

Website

www.atscale.com

Vendor Details

Company Name

FirstEigen

Founded

2015

Country

United States

Website

firsteigen.com/databuck/

Product Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Data Fabric

Data Access Management
Data Analytics
Data Collaboration
Data Lineage Tools
Data Networking / Connecting
Metadata Functionality
No Data Redundancy
Persistent Data Management

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

Product Features

Big Data

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Data Governance

Access Control
Data Discovery
Data Mapping
Data Profiling
Deletion Management
Email Management
Policy Management
Process Management
Roles Management
Storage Management

Data Management

Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge

Data Quality

Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management

Alternatives

Kyvos Semantic Layer Reviews

Kyvos Semantic Layer

Kyvos Insights

Alternatives

Apache Kylin Reviews

Apache Kylin

Apache Software Foundation