Looking for the silver bullet in business analytics?

As an analytics platform provider, we frequently get the following requests from potential clients who are looking "BI" solutions:
Common Analytics Requests:
  1. Our current system comes with reporting and anlaytics. Can you plug into that?
  2. What we need is a data scientist.  
  3. Can you predict which customer is going to leave us next?
  4. What we need is all of our data in a visualisation engine.
  5. Can you deliver a dashboard to our executive team?
  6. What we really need is self service analytics pointing at “all” of our data sources. 
  7. Can you deliver a master data management solution for us?
  8. What we really need is something that looks good – our executives are really picky about colours.
  9. We’re going to implement Hadoop because we have a lot of data. 

Now we can do all of the above things with the Pentaho platform and easily, but when we hear these types of requests we try to share there is more to implementing business analytics than just these single issues they are describing.  pentaho-logo-cmyk

These silver bullet solutions are just the tip of the iceberg when it comes to the true analytics needs of an organisation.  Organisations need to build up an analytics capability that sits across of their functions, aligned with the business and strategic goals.  

There are two sides of this analytics capability that needs to be addressed: 

 1.  Information Presentation – data discovery, visualisations, dashboards, operational reports

  - This provides employees across the organisation with information to make better business decisions

 2.  Data Management – data integration, data transformation, data blending, data experimentation and data cleansing

  -  This provides the organisation with the ability to pull data together from lots of disparate data sources

There are great individual tools that answer each of these questions separately, but are very few that treat these elements as two sides of the same analytics coin.  

This is why we are advocates of the Pentaho platform, because it has great tools on both sides of the analtyics coin.  This means that as organisations realise that they need to get consistent scalable value from their data assets, they have a platform that can facilitate building a broader strategic information asset.  In other words, when you use Pentaho to solve one of the point solution, you are also taking the first step down the path of building a long term analytics capability that can scale with your business.

The next blog post will be focused on building a Mongo schema and connection from scratch – not just using the examples. 

Most widely used Big Data? The answer will shock you!

Big data is a buzzword that gets thrown around a lot. There are oodles of different definitions out there, and the term gets applied to a range of data from digital sources to more traditional forms. Yet, at its core big data is essentially any large data set that can range in size depending on the capabilities of the business managing the data and the methods that are being used to process and analyse the data set. This big data can be found in many different forms and structures including structured, multi structured and unstructured data sets. Word Cloud "Big Data"

  • Structured data is found in fixed fields within a record or file such as in relational databases and spreadsheets. 
  • Multi-structured data is that which exists in a variety of formats that can be derived from interactions between people and technology such as weblog data and data from social media.
  • Unstructured data is not uniform or organised in any predetermined manner. It is usually in text heavy and is not easily interpreted by traditional databases as it does not have a pre-defined data model. Examples include metadata, documents, books and even audio and images. 

In addition, big data can be used to describe the availability and exponential growth of this structured and unstructured data. This data can then be used as a tool for analysis and informed decision-making.

Is there a better way to look at big data?
The team here at BizCubed recently attended a briefing with Forrester and Pentaho about big data for financial services. Access the webinar here.
During the briefing we heard an interesting alternative definition for big data:

“ Big data is the practices and technology that close the gap between the data available and the ability to turn that data into business insight”

This got us thinking! We concluded this is not only a really usable definition of big data, but we also think it describes activities going on in every business at almost every level today.

Analysing big data using this definition.
Big data differs from regular data because of its sheer size and the rate at which it can accumulate. In 2012, about 2.5 exabytes of data were created each day, and this number is likely to have doubled by 2015. This means that some companies (such as Walmart in the US) are working with data sets the size of many petabytes. To put these numbers in perspective an exabyte is around one thousand petabytes and a petabyte is around one million gigabytes- which, if printed, would equate to millions upon millions of filing cabinets full of documents.

This may seem quite intimidating, especially if you are just starting out with big data, but up close big data, like any data, is a series of points or dots that on their own have very little value. When you put the dots together and step back, you can begin to see the patterns the data points make. The insights gained through analysis of this data can lead to improved efficiency and day-to-day running of a business.

For most businesses the tool that is used to close the gap between available data (what comes natively out of standard systems and processes) and the business insight that is used to run the business, is a spreadsheet.

Spreadsheets, first took off in the 1980s with the introduction of Microsoft Excel and since this time Excel has been the backbone of data collection, analysis, and reporting. This is largely because as a significant portion of the workforce already has spreadsheet skills, its ease of use, and because business users are able to construct reports without having to go to IT with requests. Excel is therefore often seen to be an easy entry pathway in to big data applications and analysis. The process involved in using Excel or a spreadsheet for big data analysis is typically is as follows:

1. A manager or executive has an idea about how to improve the business or fix a problem.
2. They wonder if the data in the company’s database supports their idea.
3. An analyst, who usually has more of a business background and skills than technical capabilities, is asked to determine if the data backs up the concept.
4. The analyst collects the data that is available to them and uses Excel to mine that data to determine if the data backs up the manager’s ideas.
5. If the ideas are implemented – then the mining process that has occurred is usually repeated in the future.

If successful, this method is usually very flexible, available to a large number of users and it provides the management team with answers quickly. However, Excel's rows, columns, and other limiting factors, have not made it a tool that is robust enough for working with big data. As we have discussed in other articles (HERE and HERE) – what it doesn’t do is provide the flexibility and scalability that organisations require to take advantage of big data sets.

Is there an alternative to spreadsheets?
Yes! This is where a Data Integration System such as Pentaho Data Integrator (PDI) can help. Like a spreadsheet, non-technical people can easily use PDI, and the end user does not need coding skills. But where Pentaho really jumps ahead of systems like Excel, is that itprovides a much more robust system for analysing the information contained in big data sets. With Pentaho, the analyst can have complete control over the entire analysis process from extracting source data, all the way to drawing out the final insights.

Key Resources 


Data statistics from:


Our free Proof of Concept Offer

BizCubed currently has a free proof of concept offer, where to help you evaluate Pentaho, we’d like to offer you one of our experts for two days. Our expert will work along side you, loading your data, making sense of it and building some impressive dashboards. This work will give you first hand experience with the tools, their power and how quickly you can deliver outcomes.

We will also provide a secure hosted environment – alternatively, we will get you things set up internally. This will provided to you free of risk and at no cost.

Click here for more information.

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DeBortoli Wines Invests in Blending Data

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De Bortoli Wines is a third generation family wine com- pany established by Vittorio and Giuseppina De Bortoli in 1928. The couple immigrated to Australia from Northern Italy, and created a winery with a foundation rooted in hard work, generosity of spirit and sharing with family and friends. De Bortoli's reputation for premium wines, including iconic dessert wine Noble One and the Yarra Valley wines, are world-renowned.


With nearly 30 brands distributed in over 70 countries, tracking sales, inventory and operations became an increasingly challenging process. Relying upon spreadsheets had become unsustainable both in terms of administrative overhead, and in terms of limitations in reporting capabilities. DeBortoli's IT department was becoming burdened with issues such as needing to handcode ETL transformations, resulting in reduced efficiency. By developing an optimised data warehouse, De Bortoli could reduce overhead costs and development time. 

Download the case study:


Join us for a half day seminar showing how Pentaho is revolutionising the way BI applications are built and deployed. In Sydney on Tuesday, October 26th and in Melbourne on Thursday, October 28th

BizCubed is presenting free workshops in Sydney on Tuesday, 26 October 2010 and in Melbourne on Thursday, October 28 2010. Click here to register. Get in early as space is limited to 20 guests for each workshop.

When: 08:30 am – 12:30 pm, Tuesday 26 October 2010
Where: Yangtze Room, Mezzanine Level, 3 Spring Street, Sydney NSW 2000 [view map]

When: 08:30 am – 12:30 pm, Thursday 28 October 2010
Where: Conference Room, Christie Corporate, 454 Collins Street, Melbourne VIC 3000 [view map]

Upon completion of this workshop, you will have a solid workable framework for how to quickly and cost effectively arm your IT and business managers with the information they need to make the right decisions to grow your business and keep it competitive.