No-code ETL for            

Integrate Any NoSQL DB  
to 
generate Insights

And many more

Big data made easy for BI analysts & Data scientists

 

BigBI brings the full power of the distributed Apache Spark™ platform to the hands of data professionals

No programming is needed

No lengthy, weeks-long R&D cycles

Great for processing Big data

BigBI is a drag & drop ETL with the full benefits of Apache Spark™

Powerful

Distributed in-memory cluster processing, up to 100x faster than other computation platforms

Semi-structured (JSON, XML, etc.)

& non-structured

Efficient processing of semi-structured (JSON, XML, etc.) & non-structured (text, audio, image, video, etc.) data

 Batch & streaming

Handles both batch & streaming processing (Kafka, Kinesis, RabbitMQ…)

The market choice

Open Source platform for Big Data processing

AI (ML & DL)

Wide support of AI (ML & DL) algorithms – just plug & play

BigBI Studio is natively built on Apache Spark enabling data professionals full access and control of their data & data pipelines

  • Visual data discovery

  • Sample processing

  • Easy Drag & Drop data pipeline creation

  • Step by step visual data pipeline debug

  • Smart running management – Spark execution monitoring, Spark execution progress, error handling & reporting

  • Deployment management & orchestration

  • All built for data professional efficiency & accuracy.

 

Like Apache Spark™ BigBI Studio is a horizontal platform. There are use cases in each vertical that has a need for Big Data analytics: media, financial services, retail & e-commerce, government & law enforcement, healthcare, telecom & cable, Industrial & utilities, mobility & automotive, smart city, IOT, and many more.

Many business functions (i.e. departments) in each enterprise would probably have Big Data analytics use cases.

Use Cases Examples

Data Professional

The most obvious users are the data professional teams (i.e. ETL, BI Analysts, Data Scientists, etc.) in corporate BI departments - wishing to integrate Big Data, semi structured, unstructured and structured data to generate their KPIs.

Marketing, Digital and Social departments

Marketing, Digital and Social departments would like to integrate insights from their customers’ digital trail into their KPIs. Using AI, Machine Learning and Deep Learning in order to enhance digital insights and provide smart recommendations, optimize commercial offering, target advertisements to specific audiences, etc.

Sales departments

Sales departments would like to use customer trails as well as information from similar customers to recommend next best offer for a customer, increase conversion rate, optimize up-sales, etc.

Service & customer experience departments

Service & customer experience departments, for example at telecom or utilities companies, would like to measure customer experience from billions of events, corelate those events with business events to improve customer satisfaction & reduce churn.

R&D departments

R&D departments would like to correlate product usage with performance measurement to identify features that needs improvements for the next product version as well as development of preventive maintenance algorithms, etc.

Law enforcement, cyber security & financial crime prevention

Security related business functions could use graph algorithms, machine learning or deep learning which are  effective in many threat identification & incident management use cases

Natural Language Processing (NLP) for Customer care, HR or Billing departments

Smart analysis of text while deploying Natural Language Processing (NLP) algorithms. For example, ingestion of scanned documents or social media text is needed to deploy CV analysis in HR applications. Customer care analysis while could benefit from processing customer free text feedbacks, sentiment analysis of product feedbacks, etc.

Billing departments, for example in the healthcare industry, would like to use NLP + ML for analysis of patient billing documents in order to ensure correct billing codes are accurately applied and prevent revenue leakage.

 

Fast Meaningful Results From Your Big Data
(Data Lake)

  • Integrate Big Data into your enterprise

  • Deduce valuable insights from Big Data in a very short time

KPIs Deployed
within Days

  • Stop losing precious months and deploy your KPI creation in day/s with BigBI Studio

Enterprise-Grade Solution For Big Data Processing

  • Manage and Monitor enterprise data life-cycle

  • Data governance & Data Lineage

  • Security & Audit

* Apache Spark, Spark, Apache, Cassandra, Apache HBase, HBase, Haoop, & respective project logos are either registered trademarks or trademarks of, The Apache Software Foundation (ASF) . Elasticsearch is a registered trademark of Elasticsearch BV. Couchbase is a registered trademark of Couchbase, Inc. RavenDB is a registered trademark of Hibernating Rhinos and/or its affiliates. MongoDB is a registered trademark or trademark of MongoDB Inc. Redis is a trademark of Redis Labs Ltd. Amazon Redshift is a registered trademark or trademark of Amazon Inc. Google BigQuery is a tademark of Google Inc. ArangoDB is a registered trademark or trademark of ArangoDB GmbH OrientDB is a registered trademark or trademark of Callidus Software Inc. Neo4j is a registered trademark of Neo Technology, Inc. The MarkLogic name is a registered trademarks of MarkLogic Corporation RethinkDB is a trademark of The Linux Foundation
 

Any rights for the usage of any of those trademarks and respective logos are reserved to the owners. Usage of any of the above trademark does not entail any specific certification or other relationship with the relevant entity, unless otherwise specified.