Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Cloud Datalab is a user-friendly interactive platform designed for data exploration, analysis, visualization, and machine learning. This robust tool, developed for the Google Cloud Platform, allows users to delve into, transform, and visualize data while building machine learning models efficiently. Operating on Compute Engine, it smoothly integrates with various cloud services, enabling you to concentrate on your data science projects without distractions. Built using Jupyter (previously known as IPython), Cloud Datalab benefits from a vibrant ecosystem of modules and a comprehensive knowledge base. It supports the analysis of data across BigQuery, AI Platform, Compute Engine, and Cloud Storage, utilizing Python, SQL, and JavaScript for BigQuery user-defined functions. Whether your datasets are in the megabytes or terabytes range, Cloud Datalab is equipped to handle your needs effectively. You can effortlessly query massive datasets in BigQuery, perform local analysis on sampled subsets of data, and conduct training jobs on extensive datasets within AI Platform without any interruptions. This versatility makes Cloud Datalab a valuable asset for data scientists aiming to streamline their workflows and enhance productivity.
Description
The BigQuery Connector for Jira is an integration tool that facilitates the seamless transfer of Jira data into Google BigQuery, enabling extensive analysis and reporting without the need for coding. This tool allows users to export a variety of Jira data, including standard fields, custom fields, historical data, and agile metrics, along with information from the Tempo suite—including Timesheets, Capacity Planner, and Financial Manager—as well as other applications available in the Marketplace. It also features built-in calculated fields like Time in Status and Time at Assignee, making it easier to analyze performance metrics. Users can filter data using basic options or JQL, set up automatic refresh schedules, and ensure their BigQuery datasets are always current without any programming effort. The system also includes granular permissions and sharing settings to ensure that data access aligns with user roles effectively. Designed specifically for enterprise, government, and educational institutions, it supports teams that are engaged in analytics utilizing a cloud data warehouse. Additionally, the BigQuery Connector for Jira is a component of Tempo's Strategic Portfolio Management (SPM) suite, which also includes tools like Tempo Structure PPM, Timesheets, Capacity Planner, and Financial Manager, enhancing the overall analytics capabilities across various sectors.
API Access
Has API
No
API Access
Has API
No
Screenshots View All
No images available
Integrations
DataLab
Yes
Google Cloud BigQuery
No
Google Cloud Platform
Yes
Google Workspace
Yes
Jira
No
Jupyter Notebook
Yes
Integrations
DataLab
No
Google Cloud BigQuery
Yes
Google Cloud Platform
No
Google Workspace
No
Jira
Yes
Jupyter Notebook
No
Pricing Details
No price information available.
Free Trial
Yes
Free Version
No
Pricing Details
$10/month/user
Free Trial
Yes
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
Founded
1998
Country
United States
Website
cloud.google.com/datalab
Vendor Details
Company Name
Tempo Software
Founded
2009
Country
Iceland
Website
www.tempo.io/products/bigquery-connector-for-jira
Product Features
Data Analysis
Data Discovery
No
Data Visualization
No
High Volume Processing
No
Predictive Analytics
No
Regression Analysis
No
Sentiment Analysis
No
Statistical Modeling
No
Text Analytics
No
Data Visualization
Analytics
No
Content Management
No
Dashboard Creation
No
Filtered Views
No
OLAP
No
Relational Display
No
Simulation Models
No
Visual Discovery
No
Machine Learning
Deep Learning
No
ML Algorithm Library
No
Model Training
No
Natural Language Processing (NLP)
No
Predictive Modeling
No
Statistical / Mathematical Tools
No
Templates
No
Visualization
No