OpenLink Partners with Tableau to Bring Rapid-Fire Business Intelligence & Analytics to Energy Trading & Risk Management


the global leader in Energy, Commodities and Treasury trading systems,

and Tableau Software, a global leader in rapid-fire, easy-to-use

business analytics software, today announced a partnership to bring data

analytics to the Energy Trading and Risk Management (ETRM/CTRM) market.

Tableau, combined with OpenLink's CubeIntelligence,

centralizes and streamlines the collection of data from multiple

locations, making it easier for users to analyze their data, create

dashboards and reports. People have access to powerful data analytics

software that delivers reporting and analytics real-time and on-the-go,

directly to their mobile device or laptop. Users are able to examine

multiple data sources together in a single view and streamline

reporting, reducing manual labor and potential errors.

Gartner's 2014 Magic Quadrant positions Tableau as a Leader for Business

Intelligence and Analytics Platforms¹, and the Energy Risk Software

Rankings 2014 votes OpenLink the Best

Overall Energy Trading and Risk Management Platform.

David Priestley, Managing Director, Business Intelligence, OpenLink

commented "We are delighted to partner with Tableau to offer Energy

companies the tools to make data discovery and reporting easier and

faster to manage their exposure, comply with regulatory requirements and

maintain their competitive edge."

"OpenLink shares our mission to help people see and understand their

data," said Dan Jewett, Vice President of Product Management at Tableau

Software. "This partnership will help us to bring rapid-fire analytics

to companies in the Energy industry, which faces some of the classic

challenges in accessing and making sense of its data."

Chris Mudry, Chief Risk Officer, Mercuria Energy said "CubeIntelligence

is currently deployed in Credit Risk, Position Management, Commodity

Flow and Treasury. The partnership

with Tableau has added a new dimension allowing us to create some

really sophisticated clear visualisations for our business leaders."

¹ Source: Gartner (2014) Magic Quadrant for Business Intelligence and

Analytics Platforms Report, Rita

L. Sallam, Joao

Tapadinha,| Josh

Parenteau, Daniel

Yuen, Bill

Hostmann, February 20, 2014

- ENDS -

Gartner does not endorse any vendor, product or service depicted in

its research publications, and does not advise technology users to

select only those vendors with the highest ratings or other designation.

Gartner research publications consist of the opinions of Gartner's

research organization and should not be construed as statements of fact.

Gartner disclaims all warranties, expressed or implied, with respect to

this research, including any warranties of merchantability or fitness

for a particular purpose.

About Tableau

Tableau Software (NYSE: DATA) helps people see and understand data.

Tableau helps anyone quickly analyze, visualize and share information.

More than 23,000 customer accounts get rapid results with Tableau in the

office and on-the-go. And tens of thousands of people use Tableau Public

to share data in their blogs and websites. See how Tableau can help you

by downloading the free trial at

Tableau and Tableau Software are trademarks of Tableau Software, Inc.

All other company and product names may be trademarks of the respective

companies with which they are associated.

About OpenLink

Founded in 1992, OpenLink (

is the global leader in Transaction Lifecycle Management (TLM) software

for the commodity, energy and financial services industries. OpenLink's

products address portfolio management, trading, risk management, and

operations processing for both financial and physical assets.

Owned by leading private equity investment firm Hellman & Friedman,

OpenLink Tableau Case Study is a global software and services business that has grown both

organically and through strategic acquisitions, to achieve revenues in

excess of $300 million. The company serves over 500 clients, including

12 of the world's largest commodity and energy companies, 9 of the

largest financial institutions, and 11 of the largest central banks.

OpenLink has 1,200 employees in 12 global offices on five continents,

with headquarters outside New York City and field offices in Houston,

Manhattan, London, Berlin, Vienna, Toronto, São Paulo, Mexico City,

Singapore, Dubai and Sydney.

OpenLink has received numerous industry awards and recognition,

including citations as the industry leader by a number of analyst firms,

and first-in-class ranking by Energy Risk magazine for

Commodity/Energy Trading and Risk Management (C/ETRM) systems.

Learning | Tableau Software


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Big Data: Does Size Matter?

Big Data: Does Size Matter?

Timandra Harkness

Bloomsbury Press

175 Fifth Avenue, Suite 315, New York, NY 10010

9781472920058 $27.00

Big Data: Does Size Matter? is expressly for readers of all

backgrounds--no advanced mathematical or computer science knowledge is

required to learn from this straight-talk introduction to what "big

data" really What is MDM? is, and what it means both for individual people and

society at large. Broadcaster and comedian Timandra Harkness reveals how

Big Data enables greater efficiency than ever before possible, from

predicting crimes to tailoring advertisements. But can big data grow so

large as to infringe on individual rights, or even undermine a

democratic society? "Many people have pointed to the hypocrisy of

governments who want us to acquiesce to mass surveillance while trying

to reduce their own accountability through Freedom of Information acts

and the like. If we are to be watched and eavesdropped upon by the

state, should we not by default be able to access data collected about

us, or about the activities of the authorities themselves?" A

thoughtful, reader-friendly assessment of an ongoing, revolutionary

change, Big Data: Does Size Matter? is highly recommended especially for

public and college library collections.

COPYRIGHT 2016 Midwest Book Review

No portion of this article can be reproduced without the express written permission from the copyright holder.

Copyright 2016 Gale, Cengage Learning. All rights reserved.

How to Do Big Data on a Budget?

To really make the most of big data, most businesses need to invest in some tools or services - software, hardware, maybe even new staff - and there's no doubt that the costs can add up. The good news is that big data doesn't have to cost the Earth and a small budget needn't prevent companies from stepping into the world of big data. Here are some tips and ideas to help keep costs down:

Think about your business objectives

Too many businesses focus on collecting as much data as possible which, in my view, misses the whole point of big data. The objective should be to focus on the data that helps you achieve your strategic objectives. The whole point of big data should be to learn something from your data, take action based on what you've learned and grow your business as a result. Limiting the scope of your data projects so they tightly match your business goals should help keep costs down, as you can focus only on the data you really need.


Make use of the resources you already have

Before you splash out on any new technology, it's worth looking at what you're already using in your business. Some of your existing infrastructure could have a role to play. Go through each of the four key infrastructure elements (data sources, data storage, data analysis and data output) and note what related technology or skills you already have in-house that could prove useful. For example, you may already be collecting useful customer data through your website or customer service department. Or you very likely have a wealth of financial and sales data that could provide insights. Just be aware that you may already have some very useful data that could help you achieve your business objectives, saving you time and money.

Look for savings on software

Open source (free) software, like Hadoop, exists for most of the essential big data tasks. And distributed storage systems are designed to run on cheap, off-the-shelf hardware. The popularity of Hadoop has really opened big data up to the masses - it allows anyone to use cheap off-the-shelf hardware and open source software to analyse data, providing they invest time in learning how. That's the trade-off: it will take some time and technical skill to get free software set up and working the way you want. So unless you have the expertise (or are willing to spend time developing it) it might be worth paying for professional technical help, or 'enterprise' versions of the software. These are generally customised versions of the free packages, designed to be easier to use, or specifically targeted at various industries.

Take advantage of big data as a service (BDaaS)

In the last few years many businesses have sprung up offering cloud-based big data services to help other companies and organisations solve their data dilemmas. This makes big data a possibility for even the smallest company, allowing them to harness external resources and skills very easily. At the moment, BDaaS is a somewhat vague term often used to describe a wide variety of outsourcing of various big data functions to the cloud. This can range from the supply of data, to the supply of analytical tools which interrogate the data (often through a web dashboard or control panel) to carrying out the actual analysis and providing reports. Some BDaaS providers also include consulting and advisory services within their BDaaS packages.

BDaaS removes many of the hurdles associated with implementing a big data strategy and vastly lowers the barrier of entry. When you use BDaaS, all of the techy 'nuts and bolts' are, in theory, out of sight and out of mind, leaving you free to concentrate on business issues. BDaaS providers generally take this on for the customer - they have everything set up and ready to go - and you simply rent the use of their cloud-based storage and analytics engines and pay either for the time you use them or the amount of data crunched. Another great advantage is that BDaaS providers often take on the cost of compliance and data protection - something which can be a real burden for small businesses. When the data is stored on the BDaaS provider's servers, they are (generally) responsible for it.

It's not just new BDaaS companies which are getting in on the act; some of the big corporations like IBM and HP are also offering their own versions of BDaaS. HP have made their big data analytics platform, Haven, available entirely through the cloud. This means that everything from storage to analytics and reporting is handled on HP systems which are leased to the customer via a monthly subscription - entirely eliminating infrastructure costs. And IBM's Analytics for Twitter service provides businesses with access to data and analytics on Twitter's 500 million tweets per day and 280 million monthly active users. The service provides analytical tools and applications for making sense of that messy, unstructured data and has trained 4,000 consultants to help businesses put plans into action to profit from them.

As more and more companies realise the value of big data, more services will emerge to support them. And competition between suppliers should help keep subscription prices low, which is another advantage for those on a tight budget. I've already seen that BDaaS is making big data projects viable for many businesses that previously would have considered them out of reach - and I think it's something we'll see and hear a lot more about in the near future.

Businesses of all shapes and sizes, and on almost any budget, can still make use of big data. My new book Big Data for Small Business For Dummies is packed with ideas and information on how to get started with big data, along with real-life examples from a wide range of sectors.

This Blogger's Books and Other Items from...


what does it mean BIG DATA ?

Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization, and information privacy. The term often refers simply to the use of predictive analytics or other certain advanced methods to extract value from data, and seldom to a particular size of data set. Accuracy in big data may lead to more confident decision making. And better decisions can mean greater operational efficiency, cost reduction and reduced risk.

Relational database management systems and desktop statistics and visualization packages often have difficulty handling big data. The work instead requires "massively parallel software running on tens, hundreds, or even thousands of servers". What is considered "big data" varies depending on the capabilities of the users and their tools, and expanding capabilities make big data a moving target. Thus, what is considered "big" one year becomes ordinary later. "For some organizations, facing hundreds of gigabytes of data for the first time may trigger a need to reconsider data management options. For others, it may take tens or hundreds of terabytes before data size becomes a significant consideration."

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