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Big Data at Cloud Scale

This white paper will show you how Pentaho helps deliver the promise of Big Data in the Cloud with the following unique capabilities:

Flexible data transformation and orchestration for cloud-based Big Data stores, including hosted Hadoop distributions and Amazon Redshift
Drag & drop ETL design for Big Data, including MapReduce workflow
Auto-modeling and auto-publishing of analysis models for Amazon Redshift and other analytical databases
The full spectrum of cloud-friendly end-user analytics, including visualization, ad hoc analysis, reporting, and dashboards

Architected Blended Big Data with Pentaho

It has become apparent that the real value of big data is not the data in and of itself, but in the combination of data with other relevant data from existing internal and external systems and sources. For this you need to blend data to derive maximum value which as more data types are added.

How Big Data architectures are evolving
Why blending at the Source Matters
Accurate, Blended Big Data Analytics
How Pentaho is architected for the future

Paths to Big Data: Use cases, how organizations are implementing, and how to drive value

Considering a big data project? Download this eBook to discover the most common big data use cases that organizations are implementing, how to drive value with big data technologies like Hadoop and NoSQL, top signs your current business challenges can be address by big data solutions, and which big data path is right for your business needs.

Pentaho Business Analytics Platform

Pentaho brings together IT and business users to access, integrate, blend, visualize and analyze all data that impacts business results. It provides a spectrum of increasingly advanced analytics from reporting to data visualization and predictive analytics in a complete platform.

Pentaho Data Integration: What it offers and delivers

Pentaho Data Integration offers broad connectivity to a variety of diverse data including all popular structured, unstructured and semi-structured data sources. The Data Integration platform delivers "analytics ready" data to end users 15X faster with visual tools that reduce time and complexity.

Blueprints for Big Data Success

Some key 'Current Adoption' use cases for big data, are categorized according to the ability to generate business impact as well as level of implementation complexity which are expected to appear more often in the future.

Big Data Trends: Not Just for Big Business

The trend towards Big Data adoption is shifting beyond the big businesses. It is growing within the Small and Medium Enterprises not only in the entrepreneurial markets, but also in the companies seeking to uncover hidden commercial opportunities in the region's uncertain and volatile business climate.

Product Innovation with Big Data

Innovations with Big Data products for better focus on the day-to-day fulfilment of user requirements and project deliverables have begun to unleash actionable analysis on a variety of previously challenging data sources, including web logs, documents and text, social media, mobile devices, and industrial sensors.

Eliminating Complexity to Ensure Fastest Time to Big Data Value

Biggest challenges many companies face now is dealing with difficult, new and complex technologies. Examining a typical big data analytics process work flow helps identify where many of these potential problems may occur, special skill sets are required and delays are introduced.

Business Analytics Quick Start Data sheet

The Quick Start is focused on building out specific end user deliverables based on Pentaho tools while using a best practices architecture and design. After the onsite engagement, the customer is provided with a set of reports and dashboards that can be used immediately.

Customer 360-Degree View: Customer touch points and how to identify revenue opportunities

Read why blending a variety of operational & transactional data sources to create an on-demand analytical view across customer touch points can help reduce customer churn and identify new revenue opportunities.

Build a Streamlined Data Refinery

A Streamlined Data Refinery architecture represents a flexible, economical way to process and automate delivery of information to large numbers of users for a variety of analytic purposes.