Data Integration

Organizations face an increasing challenge to manage and extract value from a growing variety and volume of data. With Pentaho Data Integration (PDI), organizations can access data from complex and heterogeneous sources and blend it with existing relational data to produce high quality ready-to-analyze information – all without writing a line of code. A rich graphical user interface paired with a powerful multi-threaded transformation engine offer high performance ETL (extract, transform and load) capabilities that cover all data integration needs, including big data ingestion and processing.

PENTAHO DATA INTEGRATION PROVIDES

Intuitive drag and drop interface to simplify the creation of analytic data pipelines 

Broad connectivity to virtually any data source, including flat files, RBDMS, big data, APIs, and more 

Integration with transactional databases including Oracle, DB2, Postgres, MySQL, and others 

Access to data in enterprise applications including Salesforce.com, Google Analytics, and more 

Rich library of pre-built components to access, prepare, blend, and cleanse data 

Direct access to complete analytics, including charts, visualizations, and reporting from any step of PDI 

Robust orchestration capabilities to coordinate complex workflow, including scheduling and alerts 

Integration of advanced analytic models from R, Python, and Weka into the data flow 

Enterprise-grade administration, scalability, and security capabilities

EMBEDDED CUSTOMER REPORTING

EMBEDDED CUSTOMER REPORTING
– Developing a standardised set of rules for integrating multi-format price lists
– Automating the integration across price list and stock systems
– Remove the manual risks and time taken with manual inputs

A KNOWLEDGE COMPANY

A KNOWLEDGE COMPANY
– Provide your customers with key performance indicators
– Understand how you perform against your competitors
– Access several reporting options depending on how deep you want to go
– Adding future value and supporting revenue streams to your service

DATA PIPELINE TO REGIONAL ANALYSTS

  • A global online travel company required their regional analysts to standardise on the right data supporting global reporting standards and governance.
  • Removed the time and effort taken to manage data assets effectively across region and apply a hierarchal release structure
  • Developed a shared data modelling and analysis framework  by gaining understanding of how different regions developed analysis for their users and leveraging expertise across all teams
  • Ingesting and transforming data from many locations and working extensively with Hadoop, and different distribution engines.
  • Replacing a number of existing tools which had been hand cranked to meet ETL type requirements and applied standard working processes releasing high level skills for more effective activities

INTERNAL KNOWLEDGE DEVELOPMENT

INTERNAL KNOWLEDGE DEVELOPMENT
– Creating a new revenue stream
– Standardising analytics framework
– Reducing on-boarding time, effort and costs
– Analysts are providing insight and not preparing data

AUTOMATING PRICING STUCTURES

AUTOMATING PRICING STUCTURES
– Developing a standardised set of rules for integrating multi-format price lists from suppliers
– Automating the integration across price list and stock systems
– Creating inputs for changes and outputs for checks
– Removing the manual risks and time taken with manual price list inputs

BENCHMARK COMPARISON DASHBOARD

BENCHMARK COMPARISON DASHBOARD
– Provide our customer’s customer with key customer journey performance indicators
– Understand performance against competitors
– A managed solution supporting the agile business development process
– Adding future value and supporting revenue streams to your service

TRANSITION FROM A LEGACY APPLICATION

TRANSITION FROM A LEGACY APPLICATION
– Reducing the risks in complexity and transition time in adopting a new CRM platform
– Delivering one front-end interface to connect several back end systems
– Consistent user experience throughout transition
– Future proofing technology changes by managing a single version of data