Upgrade UNV to UNX? SQL Server? SSIS? Windows?

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Is it time to do that upgrade to UNX? SQL Server? Windows? SSIS? All of the above? If its got you a little worried, perhaps the following story will help you decide.

One of our key products is end to end Business Intelligence support, where we “own” the ongoing support, maintenance and upgrade of the BI stack. One client, the local offices of a global media distribution company, is one of our MS SQL, SAP Business Objects stack with some MS Power Platform and Tableau customers. Over the course of the last year, we delivered the following projects :-

1. Upgraded their MS SQL platform from 2014 to 2017.
2. Upgrade their BusinessObjects platform from 4.1 to 4.2.
3. Converted their SSIS ETL system from file to server and to project based.
4. Upgraded their Windows platform.
5. Migrated their reports to UNX from UNV.
6. Developed a Management Toolsuite to ensure consistent management of the environment.
7. Enhanced the performance through addition of aggregated tables and datamarts.
8. Developed a complete financial planning and analytics system that integrates three different source businesses financial data.

Projects like these are not to be taken lightly. This client has one of the highest security requirements in the industry, where just accessing a server needs specialist equipment, three factor authentication and is monitored at multiple layers. Over 300 reports across 12 universes distributed to hundreds of users with access to over 10 years worth of transactional data that is in the 100’s of millions of records, the installation is not insignificant. The data represents multiple organizations and different source systems and calendars and is very complex, integrating SAP data with third party data into a single data warehouse.

After the dust settled we received the following from the client:- “I ran all of my reports this morning which meant amending the parameters of each and they only took minutes. The (one) report returns 3.9m rows and took no more than 10 minutes to arrive in my Outlook inbox. The old UNV Versions took considerably longer and at times it was difficult to schedule them as the query prompt would take ages to appear or not at all. These reports and my new comparative report show that the upgrade to UNX was worth the effort.”

The above compliment came from one of the most technically complex financial users. This user is one where if they raise a ticket with support, you can be sure that all basic and intermediate level options are exhausted, plus a heap of advanced ones. The solution will not be obvious. They are also responsible for a major area of business, working in a senior finance role. That is why this is such a great response.

6 mistakes companies make when looking for Decision Support

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  1. Believe the hype.

Examples: Visualisation Tools vendors that ‘demonstrate’ how their tool will solve all your problems but never really show you the data wrangling requirement to get those flashy graphs to work. Or how you can distribute insight cheaply. Or how to make it truly dynamic. Or what access to it would cost for a large userbase.

  1. Listen to Buzzwords.

Examples: Machine Learning. Story telling. Artificial Intelligence. Extract Load Transform. Visualisation. Data lakes. Data swamps. Big data. Data Science. Data Engineering. Again while there are many valuable elements that fit these terms in a healthy Business Intelligence strategy, many are probably not needed or wanted for most fo your decision support requirements.

  1. Skip the Business Analysts (or misunderstand the role)

Examples: No proper discussion with business groups on what they require. No determination on the companies first and most critical Decision Support need. No analysis of the existing system for design flaws, redundancy and aging, and systematic and technical decay of business rules implemented in crisis.

  1. Big bang approach.

Examples: Expect the project to run start to finish and deliver everyone’s needs. Common to this is forgetting how long a complete project would take and how much the business through market pressures could change in this time. Also larger consulting companies promote big bang approaches because the paperwork alone keeps them in cream for years.

  1. Rigid thinking/ acceptance of rigid thinking.

Examples: Not building in organic growth and shrinkage mechanisms in the data core. Not considering the management tools needed to keep the system fresh and adjusted to needs. Thinking the data warehouse will be the same for the next 20 years.

  1. ERP blindness (lazy thinking, risk averse thinking)

Examples: Assuming an ERP will do everything the vendor promises, including Business Intelligence. Assuming the ERP will perform all the functions of the business as you need. Forgetting that having the same ERP as competitors means you lose competitive flexibility.

Try a different approach.

  1. Start with understanding your business users, the coalface departments. Define the role data plays in their work. Look for the lowest hanging fruit, what decision support capabilities wins you the most market value.
  2. Load only the data that knowledge thread requires, staged, transformed, and data marted to meet your users immediate needs. Select the tool they will find most appropriate.
  3. Add the next most important need, scaling the data warehouse core tables horizontally while adding a new DataMart vertically.
  4. Keep going with connecting source systems to business user needs based on your original model as defined by the business and horizontally scaling the data warehouse.

The advantage of this approach is numerous, but the biggest is the saving ion time and money. You get reports in days and weeks, not months. You get a core operational data store that is aligned to source and user needs simultaneously. You get an organically managed data system that allows you to kick source systems to touch and replace them with minimal disruption.

We should know. We have being doing this for 15 years. Through a global financial crisis, a recession and a pandemic.

Women Festival

International Women’s Day

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International Woman’s Day was yesterday which was also a public holiday in Victoria Australia, where we at Triatin have our head office. This is a good time to reflect on how well we do at promoting equality in the workplace, but first a shout out to the great women past and present that have made and still make Triatin successful over the last 14 years. Here is the analysis.

Triatin is 60% female, and our leadership team is 80% female. Our highest paid team members are women. Our lead data scientist is female, our operations director is female, our staff morale lead is female and our financial controller is female.

Our teams are diverse, over the years hailing from China, Thailand, South Africa, Australia, India, Zimbabwe, Brazil, Germany, The UK, Canada, New Zealand, Pakistan, Russia, France, Turkey, the Philippines, Indonesia, Singapore, Hong Kong, Mongolia, Nepal, Bangalore, Sri Lanka, Egypt, Israel and more. Some have disabilities. Some come from poor backgrounds and some from wealth.

However it is very important to note, that none of this actually matters. Their gender, ethnicity etc. is coincidental. They are not here as “equality hires” and we are not blowing our horn about the companies gender profile. Nor does their heritage. Or religious affiliation. Or political stance. It would be nice to think our success is borne in our diversity, but that is not the reason.

The reason for our success can be summed up in one word. Competence. We have had many people of all genders work with us over the past, all highly competent people. We don’t see the gender, race, life status, physical ability as important criteria for hiring people. We look merely at competence. Will they be able to deliver the quality of service that our clients expect?

The difference between us and many other companies is that we see past the gender, past the assumptions of competence, past the traditions. We look at partnerships with out team members, we are social enterprise where we share the successes and failures of the business across the board. Our people don’t see gender in each other, they see competent colleagues who they can trust to be fair and supportive.

Try it. Look past the gender. Look past the diversity. You may be surprised at how much happier your teams are. And yes, you will find your gender and diversity profile automatically adjusts to a more balanced, more equitable blend. Just actually put your prejudices aside instead of pretending to.

Hope your International Woman’s Day gave you pause for thought. And your thoughts were as pleasant as ours.


Executive Reporting and Analysis – Automate Boardroom Reporting!

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Executive Shareholder and Public Reporting System

What it is

A Triatin IT Metrics Datamart solution is a complete Executive Information Systems solution, with the ability to serve up dashboards, performance reports, balanced scorecards and even the entire Annual Report pretty much automatically.

How it works

By storing the data as metrics already,  the reports no longer need to calculate the values from the source system. That is done by the load systems, which include capabilities for automated loading for structured data as well as quick easy manual loading through a capture screen.

Metrics are identified by type

  • a currency or a percentage or a volume for example, by period
  • a year to date, month to date or rolling year value for example and by subject
  • a P&L value or a Cash flow Value per business division, subsidiary location or department.

This way any common or uncommon metric can be created and loaded against any business entity; whether its P&L metrics,  Revenue Statement, Performance or even  Sustainability.


The metrics datamart solves a number of persistent issues in so many business settings:-

  • Timely clean EIS reports and data
  • Easy integration with Corporate Websites
  • Retained History of old or changed metrics
  • Quick Generation of Annual Reports
  • Quick generation of balanced scorecards
  • Dashboards Friendly

Technical Details

Using a relational database we load and store each metric at its completed value, against the various distinct business categories and levels.

We assist you  to develop automated load processes for structured data (e.g. accessing your own data systems or spreadsheets) , or  you can also capture, edit and maintain metrics directly in the system through our GUI capture application

We then assist you in developing reports and dashboards using your own  tools like MS Excel.*

Who We Are

Name dropping

Triatin boasts an impressive list of clientele, including some of Australia’s biggest names

Sony Pictures Home Entertainment, Members Equity Bank, Department of Human Services, Madison Cross, Australian Leisure and Hospitality, Billabong,  Bakers Delight, Pfizer, APHS, ANZ Bank, CGU, Corporate Investigations, Queensland University of Technology, Universal Music , Wesley College.