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features
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Description

Bipp's cloud BI platform, built on the innovative bippLang data modeling language, was crafted specifically for SQL and data analysts from its inception. It enhances productivity for teams, equipping businesses to make quicker and more informed decisions. The bippLang data modeling language simplifies SQL queries by enabling the creation of reusable, intricate data models that incorporate custom columns and dynamic sub-queries. With Git-based version control, analysts can work collaboratively, ensuring that all data models and SQL queries are consistently backed up. The always-free version provides access to a robust BI platform with professional support at no charge. In-database analytics eliminates the need to transfer data to another system, accelerating access and yielding real-time results. The auto-SQL generator intelligently utilizes defined joins in the data model to determine which tables to combine and dynamically generates sub-queries based on the context. Furthermore, the single source of truth data models guarantee that every individual in the organization relies on identical data for their business decisions, fostering consistency and reliability across the board. This comprehensive approach not only enhances collaboration but also solidifies the foundation for smarter strategic planning.

Description

Python-SQL is a library designed to facilitate the writing of SQL queries in a more Pythonic manner, supporting a variety of functionalities such as basic selects, selections with where clauses, and complex joins including multiple joins. It allows for groupings and output naming, alongside ordering results and executing sub-selects, while also enabling queries on different schemas. The library is capable of performing insert operations with default values, specific values, or even using another query for insertion. Furthermore, it accommodates updates with specified values, conditions, or lists, as well as deletions based on conditions or sub-queries. Additionally, it offers different query styles including limit style, qmark style, and numeric style to cater to diverse programming needs. This versatility makes Python-SQL a powerful tool for developers working with databases in a Python environment.

API Access

Has API No 

API Access

Has API Yes 

Screenshots View All

Screenshots View All

Integrations

Amazon Redshift Yes 
Domino Enterprise AI Platform No 
Git Yes 
Google Cloud Platform Yes 
Hive Data Yes 
Impala Yes 
Kylo Yes 
Microsoft Excel Yes 
MongoDB Yes 
MySQL Yes 
Oracle Cloud Infrastructure Yes 
PostgreSQL Yes 
Python No 
SQL Server Yes 
Snowflake Yes 
Teradata VantageCloud Yes 
Visplore No 

Integrations

Amazon Redshift No 
Domino Enterprise AI Platform Yes 
Git No 
Google Cloud Platform No 
Hive Data No 
Impala No 
Kylo No 
Microsoft Excel No 
MongoDB No 
MySQL No 
Oracle Cloud Infrastructure No 
PostgreSQL No 
Python Yes 
SQL Server No 
Snowflake No 
Teradata VantageCloud No 
Visplore Yes 

Pricing Details

$10 per user per month
Free Trial Yes 
Free Version Yes 

Pricing Details

Free
Free Trial No 
Free Version Yes 

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 No 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac Yes 
Linux Yes 
Chromebook No 

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) Yes 
In Person No 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

bipp analytics

Founded

2017

Country

United States

Website

bipp.io

Vendor Details

Company Name

Python Software Foundation

Country

United States

Website

pypi.org/project/python-sql/

Product Features

Business Intelligence

Ad Hoc Reports No 
Benchmarking No 
Budgeting & Forecasting No 
Dashboard No 
Data Analysis No 
Key Performance Indicators No 
Natural Language Generation (NLG) No 
Performance Metrics No 
Predictive Analytics No 
Profitability Analysis No 
Strategic Planning No 
Trend / Problem Indicators No 
Visual Analytics No 

Data Preparation

Collaboration Tools No 
Data Access No 
Data Blending No 
Data Cleansing No 
Data Governance No 
Data Mashup No 
Data Modeling No 
Data Transformation No 
Machine Learning No 
Visual User Interface No 

Product Features

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