Is design thinking catching your attention? It should. Data insights not available before now can transform your business models and allow you to lead in your industry when you incorporate elements such as predictive, mobile dashboards and machine learning. This wave of change is forcing data architects to re-think and re-design how programs and applications must be built. To truly innovate, design teams need to push the design thinking envelope on almost every project.
“You can have data without information, but you cannot have information without data.”
– Daniel Keys Moran, computer programmer and science fiction writer.
Since the invention of the first computer, the world has been on a digital light-speed journey – one that has seen massive change in how we interact with our world and with each other. Today, there are more than 2.5 billion[i] smart phones carried in people’s pockets – each more powerful than the ones used to run the spacecraft that landed the first men on the Moon.[ii] In particular, how we interact with and gain insight from data has gone through an incredible transformation. We have evolved from relying on simple historical reporting – from the days of simple reporting to now, where tanker.
The Way It Was
Reporting has always been a critical element for a business to thrive and we have been accustomed to seeing our reports – our data – in fairly standard and historic terms. Let’s take a straightforward quarterly sales report at a consumer retail company, for example. Simple data, like units sold, prices received, cost of goods, volume of shipments and so forth, would be gathered and stored over a three-month period and then used to generate a few charts and graphs. Conclusions would be drawn from this static data and the company would shift strategy based on the conclusions.
Perhaps the conclusions were accurate and maybe they weren’t. Regardless, that’s how it’s been done for a long time: based on the data available.
The Way It Is
Today, the capability exists to break down data into far greater detail, do it in real-time and through disciplines like machine learning and artificial intelligence, draw highly focused and accurate conclusions not at the end of a business quarter but at the end of each day, and, in many cases, as it happens.
Now, a business can make highly informed decisions immediately and adjust accordingly. Of course, it’s not simply analyzing a few traditional data points, like sales; it’s analyzing where those sales took place, in which store locations, even in which aisles or departments, at what time of day, from which shelf the customer chose a purchase, what the customer’s likely income level is– in other words, the more highly specialized the data, the more highly specialized and precise the conclusions that can be drawn.
Because it’s possible to generate highly detailed data and analyze it from so many different perspectives, every sector of the economy is making use of data analysis.
In the manufacturing sector, factory operations are being revolutionized[iii] by both big data and analytics. Sensors generate endless streams of data on the health of production line equipment, data that’s being examined by the minute for the slightest indication of a potential problem or defect. Conclusions are drawn and actions implemented immediately to avoid any breakdown and disruption in the production process. There’s a positive ripple effect to this: customers don’t experience delays and the company doesn’t experience a loss of revenue.
The virtually unlimited storage capacity in the cloud, coupled to highly sophisticated computer algorithms that can perform serious analysis in, literally, seconds, is placing tremendous demands on data architects. Programs and applications must be agile enough to allow for updates, added features and improvements without delay. This has meant developing new architecture that can not only run a program at lightning speed but can be altered or updated in the areas where it needs improvement, much like making incremental improvements to a car model but without re-designing the whole car every time.
Gone are the days of a monolithic software structure where data warehouses needed a year or more to be designed and several more months for data to be inputted. If missing data was discovered, it would mean an entire rebuilding of the program.
Microservices and Teams
Today, Optimus Information designs architecture so that updates, changes or improvements can be made to one area of a program or application without having to open up the whole program. By using microservices in our software development, Optimus has created functional teams whose responsibility is to just one area of a program. A team focuses only on its specific area and generates improvements without impacting other teams or resulting in an overhaul of an entire software product. Tremendous amounts of time are saved for our clients and the cost of updates or re-designs is driven down dramatically.
Optimus applies the same method to data gathering. By means of advanced tooling, our clients can store raw data, without pre-aggregating it, run a query on that raw data and have the answers they need in a matter of seconds. Previously, it would take weeks to get a result because the data would have to be assessed and compartmentalized as it was gathered and placed into structured environments before a query could be run. This is what we call modern data warehousing. The focus is on agility and speed.
Down the Road from Microsoft by Design
Optimus specializes in working with IT departments of companies that don’t or can’t spend the time and money to develop the cloud-based software architecture needed today. Optimus uses a suite of leading edge services, on the Microsoft Azure platform, that allow us to select exactly the right components to solve a client’s problem. We are physically located close to Microsoft’s Vancouver and Redmond development centres
Optimus is a Microsoft Gold Partner and, in that role, we work very closely with Microsoft on new product previews and trials that are in development, giving feedback that improves our customer’s end product. Optimus employees have often already kicked the tires on new Azure features before they are released. This keeps us at the forefront of rapidly changing technology but let’s us give feedback as enhancements are designed.
If you want to enhance and sharpen the results of your data analysis, we invite you to contact us. We are happy to explore some “what-if” scenarios with you to help propel your data insights – and your business – forward exponentially. Reach out and schedule a virtual coffee anytime.