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Think Big: How Design Plus Data Will Change Your Business

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.

IoT Changes Shipping Industry – Reduces Risk and Cost

A client that operates a fleet of tankers equipped with IoT sensors wanted to move beyond its basic data reports and drill deeper into the technical data gathered aboard its vessels. Optimus utilized elements from Microsoft’s IoT Suite, including Azure Data Factory, to create visually appealing reports and dashboards that contained information gathered from thousands of sensors throughout the fleet.

The results meant a far more in-depth data analysis than the company had been getting, delivering more accurate insight for more accurate business decisions. When it comes to tankers, a simple mistake can cost millions in terms of lost time, environmental disasters, financial penalties, missed deadlines and more.

Optimus solved the client’s existing problem while building a platform for continuous improvement with data analysis using Microsoft Azure tools. Because the data can be aggregated in the cloud, the client can analyze greater amounts of data over an extended period of time, thus further enhancing their shipboard operational analysis and implementing global cost saving efforts as a result.

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.

Best Practices for Engaging SMEs in BI Reporting Projects

working-with-SMEs-on-report-development-150x150 Best Practices for Engaging SMEs in BI Reporting Projects

Involve SMEs when gathering requirements. They know what they need!

In most report writing projects, the biggest challenge as a consultant is to quickly gain an understanding of the client’s data. A consultant needs to get a good grasp of all systems and business logic at the requirements gathering stage before embarking on report development.

It is useful working with the company’s IT department, especially in terms of understanding the use and impact of the chosen technologies/applications on the project. However, a consultant also needs to understand the business itself, which includes gathering knowledge on the company’s business model and its success drivers, KPIs, and how the report’s data will be used in monitoring and controlling these drivers.  This is very important in order to ensure that the requirements are complete and make sense, both from a technical and business perspective.

It can be challenging to gain a deep understanding of these factors if the sources of information are limited to the IT department. Meetings with subject matter experts are required to achieve depth and breadth of knowledge. Some clients do provide schema diagrams and a few sample queries, but the success of a BI engagement demands much more.

The consultant needs to make a concerted effort to find the people that know the data. These people may or may not be included in the BI project but their knowledge on how to pull the data and analyze it can be invaluable to the BI initiative. A consultant should make sure that these key players are an elemental part of the requirements gathering and testing process. These individuals can usually determine very quickly if the data is correct, reducing time wasted. Having them available as a resource throughout a BI project can not only make the requirements gathering and development process easier, it can help ensure that the data is accurate and used properly to allow for optimal business analysis.

Here are some of the key areas which these individuals can help with include:

  • Generalizing specific information obtained for a single report, which enables the consultant to anticipate future requests and be flexible in meeting client needs in the future. The knowledgeable individuals can help to define clear and clean criteria.
  • Refining specifications that are incomplete or open-ended, taking into consideration both technical and business perspectives, to reduce redundancies and repetition.
  • Reconciling the “logic-based” mindset of a programmer with the “business-based” perspective of the user. This may lead to illogical requests that generate no data.
  • Codifying generalized user requests. It is a good idea to have the user create a request in a single sentence, in the form of an actual question the report will provide the answer to. This will reduce wasted effort and allow the consultant to deliver the report in the most concise, comprehensive, and efficient format.

We are helping our clients with their report development and business analytics projects. To learn more about the report development process, connect with us. We are happy to provide free consultations.

SSRS and Crystal Reports Comparison: An Ongoing Debate

ssrs-versus-crystal-reports-150x150 SSRS and Crystal Reports Comparison: An Ongoing Debate

Two major reporting vendors in a constant race.

For the past couple of months, I have been working on reporting projects for a few clients in British Columbia that have put me in an excellent position to make a comparison of SSRS and Crystal reports. One of the clients is using SQL Server Reporting Services (SSRS) as the reporting platform for all organizational reports, including custom built Microsoft Dynamics AX. Another client is using Crystal Reports (CR) as their core Business Intelligence application.

Both SSRS and CR are business intelligence applications that take data from data sources of varied formats and generate reports providing decision support information. The reports can be interactive Web reports, tabular, graphical, free-form on-screen or print reports. For example, data can be accessed from Oracle and SQL databases, Excel spreadsheets and local file systems, and reports generated in Excel, PDF, DOC or executed right in the browser.

I have encountered many debates regarding the comparative advantages and disadvantages of SSRS and CR. The debate has been complicated by two major factors. Firstly, many of the complaints relate to earlier versions which might not be present in the latest ones. Secondly, the applications are used in varied environments for varied purposes and some might find SSRS more suited to their requirements while others might find CR the right choice.

One general objection is that CR is problematic to work with, being immense and slow. This can be the result of the peculiar challenges its development team faced within the context of ownership changes, and that too with a product designed for a very different environment.

SSRS, on the other hand provides a far more pleasing experience. However, there are complaints about it not being able to meet finer formatting requirements. Born in an earlier era, CR is more likely to come with more low-level features that enable detailed requirements.

Most users might find SSRS a better choice, which is more suited to modern environments and requirements, especially when paired with the Microsoft stack (SharePoint). On the performance front also, SSRS is likely to score much higher in most environments. On the other hand, CR has been in existence for a longer period and more people are likely to be familiar with it. And those who are finicky with the smaller details might prefer the low-level features of CR.

Day by day I am observing that the market is migrating towards SSRS. Overall, SSRS is a better choice for the modern user who is more concerned with performance and ease of use. SSRS is a server based report generation and scheduling software system that considerably reduces the time required to generate and send business intelligence reports. With SSRS one can also tailor reports to organizational needs. With customizable report templates at hand, business managers and executives can easily take full advantage of SSRS. The reports can also be published and accessed on demand. With its familiar, widely used Microsoft Office Excel interface the SSRS can be comfortably used by new employees in an organization without extensive training.

OptimusAnalytics offers both Crystal and SSRS report development. To learn more about our reporting experiences and solutions, contact me directly at rupmeet.singh@optimusinfo.com

Cloud Data Warehousing Advantages

cloud_storage-300x200 Cloud Data Warehousing Advantages

Data warehousing in the cloud

“Why create a data warehouse in the cloud?” I have been answering this question many a times when I go to networking events.

There are a number of cloud data warehousing advantages:

  • Cost savings
  • Total cost of ownership
  • Mergers and acquisitions
  • Standardization
  • Better understanding of competitive landscape
  • Improving product and service quality.

Many enterprises are finding that data warehouse appliances can significantly reduce the total cost of ownership. All resources, including expensive networking equipment, servers, IT personnel, etc are shared, resulting in reduced costs, especially for small to mid-sized applications and prototypes.

In the case of mergers and acquisitions, duplicate financial data warehouses need to be rationalized. An enterprise or government agency may want to rationalize various warehouses based on disparate warehouse technology platforms by moving to a standard platform. Cloud computing enables companies to shift money from capital expenses to operating expenses, enabling the customer to focus on adding value in their areas of core competence, such as business and process insight, instead of building and maintaining IT infrastructure.

In short, cloud computing allows you to focus your money and resources on innovating. “Regardless of the reason for the migration, in every case the reporting and analysis supported by the migrating data warehouse must continue to run seamlessly.” This is a common need expressed by my professional network. Cloud computing platforms such as  Microsoft Azure, provide many of the core services that, under traditional development models, would normally be built in house. These services, plus templates and other tools can significantly accelerate the development cycle.

“What should be the solution?” is the subsequent question that arises during conversation. “Use data visualization to insulate reporting users during data warehouse migrations” is my to-the-point answer. Additionally, data virtualization to the cloud provides a more agile integration approach that overcomes data complexity and disparate silos to provide business with the timely data it needs to meet today’s ever-changing business requirements. Provisioning-on-demand enables faster set-up and tear-down of resources on an as-needed basis. When a project is funded, you initiate service, then if the project is killed, you simply terminate the cloud contract.

Data Virtualization using cloud computing is the opposite of traditional data warehousing. The cloud is more vibrant and valuable in that it’s something elastic that customers can scale up or down with dynamic resource allocation ensuring efficient use of shared processing and storage resources. It wants data to be location independent, transparent and function shippable; whereas, the traditional data warehouse is a centralized, persistent data store. There will be a need for a run-time metadata in order to register and access data sources as a service. Growing data volumes are winning. Still, with cloud computing (as with web services), the service, not the database, is the primary data integration method.

The ability of the cloud to load data quickly allows the vendor to work with larger data sets during smaller time windows as dictated by the customer, as well as service more customers at any one time. While smaller companies may only refresh the data in their data mart weekly, larger customers typically refresh data daily. Moreover, the transactional database of such larger customers can only stay offline for short time periods during which data must be transferred to the data marts.

Data loaded in the data warehouse has to be organized in the best possible way to enable the optimal execution of queries. The managers of on-premise data warehouses and marts constantly look at the queries executed against their databases to determine how to best organize the data to achieve best query execution times. Some of these optimizations can be performed automatically by the database management system but most require manual intervention. Having full control of the database management system enables the SaaS BI vendor to better optimize the organization of the stored data.

Finally, the emotion of the language used to query the data mart in the cloud determines the range of data analyses that can be performed and reports that can be created by the business intelligence tools (like Microsoft SSRS). Cloud infrastructure also contributes to the speed with which queries are executed that generates quick analytics reports.

As a business intelligence vendor in Vancouver, OptimusAnalytics would be happy to share our experiences with you. To learn more about cloud based data warehouse solutions, contact me directly at rupmeet.singh@optimusinfo.com

(image credit: Goma on Flickr)

Retail Business Analytics Dashboard: What and How

ssrs_dashboard-300x240 Retail Business Analytics Dashboard: What and How

Real-time data summarized and graphically displayed on a single page.

Retail giants in Canada such as Canadian Tire and Nygard International are rapidly moving towards Business Analytics. The market hype around retail analytics has been building since early 2007 when predictions of the sustainability of business analytics as a vehicle of retail growth initially gained momentum.

The retail business analytics dashboard is the last important step in the analytics initiative of any organization. In this blog post, with the help of examples from the retail industry, we will be able to answer the following questions: What exactly is on a dashboard? What should it summarize? And where should it lead to?

What is a dashboard?

Any user in the organization wants to be provided a summary view of their data. Dashboards should employ a common approach and be somewhat standard for each role and responsibility across the enterprise, while accommodating individual preferences. A personalized dashboard captures what is most important to the individual user.

Knowing what is happening in your business right now is the first step to making smart decisions. Giving that insight to people across your entire organization ensures that they prioritize goals and activities based on actual performance.

A dashboard defines the language and measures by which department owners will evaluate their performance and the performance of the business. A dashboard sets the context of what individual managers should know about the organization and what problems and opportunities will require their attention. Dashboards also provide quality information to the user, far beyond the scope of individual responsibilities.

Looking at our example industry (Retail), we have seen that it is moving very fast, especially in countries like Canada. Due to the industry’s competitive dynamics, the business environment is too challenging to tolerate business analytics myopia. Well-designed dashboards insist on delivering a big picture view of the business. The big picture view provided by dashboards to particular functional areas of the business, utilizing tightly limited information, prevents BI myopia.

Without the aid of dashboards, a marketing manager might be able to track data pertinent to their distribution center, group of stores, or merchandise group but they will miss the overall trend. Therefore, Business Analytics must broaden the user’s span of understanding while empowering them to drive deeper into their own responsibilities.

What to Manage?CPCS-Backbone-of-retail-management-300x255 Retail Business Analytics Dashboard: What and How

Four primary things that all retail managers should play a role in managing: CPCS – Customer, Product, Channel and Supplier (fig 1)

Understanding what responsibilities each management role has in each of these subject areas is the key to developing good dashboards. Everyone will have access to CPCS details, but one of these perspectives will be dictated according to the manager’s role. Retail dashboards should default to the primary perspective of the business while affording users (managers) the opportunity to switch easily to one of the other three.

For example, store managers would typically view data relating to the stores for which they are responsible. The product specialist’s dashboard would typically summarize the view of their products. Buyers would typically select the supplier view, allowing them to drill down into more detailed information by products, channels, and by types of customers.

Of course, as managers begin to weave their dashboards into everyday retail activities, their needs will change. To accommodate change, you need to have technology that will grow organically with your users’ needs.

How to Manage?

The best dashboards have their frame divided into five sections: Operating Summary, Scorecard, Trends, Best and Worst Performers, Opportunities and Challenges (fig 2). This will help retail managers to get better insights and eventually assist in better decision making. Questions like “What’s going on?”, “Where do we stand?”, ”Where we are headed?”, “Where should we be working more?” are interactively answered with the help of dashboards.

Important-components-of-dashboard-300x237 Retail Business Analytics Dashboard: What and How

Important components of Retail Business Analytics Dashboard

WE ARE MAKING IT HAPPEN

OptimusBI will help you choose the right self-serve business analytics application to deliver and manage your dashboards. We will make it easy to roll them out and continually evolve them with your business. This ensures information stays relevant as the business changes, and that more users can use dashboards in everyday decision-making.

We would be happy to share our experiences with you. To learn more about how to deliver cutting-edge dashboards, contact me directly at rupmeet.singh@optimusinfo.com

(dashboard image courtesy of Dashboard Insight)