25Feb

How Much Do AI Projects Really Cost?

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Artificial Intelligence

When seeking stakeholder buy-in for your AI project, make sure to consider both AI project budgets: the one for starting up to prove a technological goal, and the one for productization.

18Feb

Do You Have The Right Team For Your AI Project?

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If you want to be successful, you need these experts to buy into your project upfront.

10Feb

Daitan Named Among AI Consultancies in Report by Forrester Research

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Daitan’s placement in the Forrester report highlights the company’s experience in AI-based product design.

02Feb

Strategies to Reduce Risks in Machine Learning Projects

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Preparing for the inherent risks in machine learning is so important in order to prove the value of ML projects for your SME.

21Jan

Poorly Defined Goals Put Your Next AI Project at Risk

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AI Project, AI Project Goals, Artificial Intelligence, Business Goals, Machine Learning

Any technical project needs clearly defined goals for the best chance at a successful outcome. When using an emerging technology, like artificial intelligence, this issue becomes even more critical.

07Jan

Stakeholder Buy-in Helps AI/Machine Learning Projects Succeed

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AI, AI Project, Business Goals, Machine Learning, Machine Learning Project

Stakeholder buy-in plays a critical role in the success of a machine learning project. Learn how early buy-in ensures your project reaches its goals.

03Dec

Comparing different types of AI/ML Partners

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AI, Data Science, Hiring, Software Development

An AI/ML project is often more challenging than an “ordinary” software project. It comes with unique risks that can threaten the desired business outcome. Given the high rate of project failures, or those that remain in “POC Purgatory” unable to be scaled into production, it’s critical for AI project owners to understand the risks they face to reach a successful product execution. In this article we will discuss one of these risks: the importance of building a team with the right skill sets

10Nov

When Engineering Builds Business Value for a Company, It Should Get Credit For It

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Business Outcome, Digital Business, Digital Transformation, Outsourcing, Software Development

I believe when engineering measures success in terms of growth-related business outcomes, the contribution to business value is significant—making it important to identify targeted outcomes at project onset, and not in hindsight as a justification for a new budget.

02Nov

Build an AI Project Team with the Right Skill Sets to Avoid Risk of Failure

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AI, Data Science, Hiring, Software Development

17Oct

Cheat sheet to quiz your ML/AI candidate partner

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AI, Risk Assessment, Risk Management, SME

No matter the industry sector, artificial intelligence and machine learning continue to transform how we do business. From AI-powered chatbots performing a customer service role, to automated financial trading algorithms, a variety of ML expert innovations are driving this digital transformation.

06Aug

Building a Great Customer Experience for Today’s Digital Business Starts With People and Leads to Better Outcomes

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Customer Experience, Digital Business, Digital Transformation

Digital Business starts with people, and it follows with developing the right engagement that delivers a delightful experience, in order for the desired business outcome to be reached.

01Aug

Still Far Apart, But Always Together

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COVID-19, Daitan

It’s been a while already, since we began working from our home offices, and we begin to feel homesick for the coffee-breaks, conversations in the hall, luncheons with the team, and so many more things that only day-to-day proximity can provide. We know that for the time being, it is for a greater good and for everyone’s...

22Jul

Building a Business Case for DevOps

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Agile, DevOps, Software Development

It is very easy to get excited about DevOps when hearing about how Google, Facebook, and Amazon have achieved incredibly short release cycles and insane levels of automation in their infrastructures. What rarely gets mentioned is how much these wonders of technology cost. The tech giants have virtually unlimited funds to invest and can obviously afford the luxury. The rest of us, however, need to fight for our budgets and choose very wisely where to invest it.

16Jun

We Are More Social While We Keep Physically Distant

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Collaboration, COVID-19, Digital Business, Digital Solutions, Digital Transformation, Remote Working, Social, Virtualization

Navigating this global pandemic has forced change none of us ever imagined. Companies had hours to pivot entire workforces into remote work settings while maintaining business continuity. As devastating as it has, and continues to be, it has also forced those businesses that can remote work to rapidly develop new behaviors and that is what I want to talk about. I think in business, we have become more digitally social whilst keeping physically distant—and based on the experience so far, it’s helped us adapt. Some may consider this to be “increased productivity,” but I think it’s bigger than that.

10Apr

Daitan Canada Part of the Global Entrepreneurial Hub Emerging in Victoria, BC

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Canada, Daitan, Daitan Hiring

Daitan's Canadian Country Manager, Mario Zimmer, is Interviewed by a popular local Victoria publication, Douglas Magazine, to explain our move to the region. Featured in their April/May edition, Mario describes some of the excellent opportunities the city provides for a growing company like Daitan and a few of the challenges created as Victoria rises to meet the influx of new businesses and people. Victoria is quickly emerging as an attractive entrepreneurial hub on the global map.

07Apr

Financial Times Names Daitan One of Americas’ Fastest Growing Companies

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Daitan, Daitan Hiring

Winning the prestigious Financial Times FT 1000 Americas' Fastest Growing Companies award exemplifies Daitan's strong growth as a technology leader across North, Central and South America.

02Apr

The Wisdom of Business Continuity Planning

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Business Outcome, COVID-19, Daitan, News

Every CEO understands the importance of Business Continuity Planning (BCP). It is a standard best practice and essential to ensuring your business continues without disruption despite “unforeseen” threats or disasters. Solid Business Continuity planning is exactly how Daitan was able to immediately react to the threat of COVID-19. Within hours we fully pivoted our entire workforce (across 2 continents) to working safely at home and without any disruption to customers.

20Mar

Daitan User Experience Design Expertise

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Design & Architecture, Full Stack, Software Development, UI/UX, User Design, User Experience

It is common to come across incorrect or incomplete interpretations of the meaning of “design” and its benefits when applied in a software development context. Design is frequently perceived only as the efforts made to improve visual aesthetics in the user interface, but for Daitan design goes far beyond that. In this article, we will discuss six reasons why Daitan Design Services are relevant to your business.

07Mar

Software Composition Analysis

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Open Source, Software Composition Analysis Tools, Software Development

Organizations that rely heavily on open source dependencies face a myriad of risks concerning the license models of each dependency, as well as, how vulnerable to threats they are. Adding a degree of code surveillance is a must for enterprises that want to mitigate financial and security risks, and brand exposure.

19Feb

Achieving Agile at Scale

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Agile, Software Development

Many organizations have benefitted from using Agile methods for individual engineering teams and single projects. However, to keep pace with the challenges of Digital Transformation, organizations are actively working to expand their use of Agile software development by adopting it across entire product portfolio(s)—covering the complete digital delivery lifecycle. This magnitude of change affects whole organizations and the culture. It’s frequently referred to as Agile at scale.

10Dec

When Business Gets in the Way of Agile Adoption

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Agile, Agile Teams, Culture

We discuss some of the challenges organizations face in terms of product and technology, as well as business leadership when working to achieve Agile at Scale. The hard work is in the day-to-day efforts, and when facing tough challenges, people want practical answers that help them accelerate implementation and become more Agile in the process. For many, the business and leadership challenges are the toughest. But, to really solve these business challenges means the difference between “doing” Agile and “being” Agile

05Nov

Programming With Data

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Data, Data Centers, Data Science, Machine Learning

In this post, I will share a very basic view of the technologies that are used to build ML solutions with the goal of helping those who have not had exposure to this domain understand where all the hype comes from. For my engineering colleagues, keep in mind that this article is meant to very simply present this technically complex field; and, does not tackle detailed technical challenges, the compelling issue of bias, and social concerns about ML/AI replacing jobs.

03Nov

How the C-Suite Can Think About Scaling Agile From an Engineering Practice to Business Value

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Agile, Best Practices

Agile isn’t just an engineering methodology anymore; increasingly it’s become a business practice—and there is a proliferation of good research, frameworks and reading material for those who seek some guidance. In this post, I would like to make 3 points I believe every senior executive should consider when it comes to scaling Agile. I’m not here to drill down on the details, but rather provide some context based on Daitan’s experience.

11Oct

The 5 Principles to Building an Application Development Security Mindset

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Application Security, Security

Building a digital business often results in creating greater surface attack areas, which increases risk of vulnerabilities. Although it feels like business initiatives for growth work at cross purposes to securing a company’s core assets, it doesn’t have to.

10Jul

How Analytics Measuring Output and Outcome Bring Value to Scaling Agile

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Agile, Analytics, Business Outcome

The movement to scale Agile across organizations has led to lots of focus on, not only best practices and methods for implementation, but also the right way to measure success. In this article, we want to discuss the distinction between Agile analytics that quantify “output” versus those that measure business “outcomes.”

10Apr

The Importance of Portfolio Management as Part of Scaling Agile

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Agile, Kanban, Portfolio Management, Value STream Mapping

Portfolio Management is growing in importance as the need to scale Agile grows, and it’s bringing positive tangible business benefits to companies large and small. So, I thought it would be valuable to take a look at Portfolio Management and share a few insights from our own knowledge base and experiences.

03Jan

Measures of Success for Growing Beyond a Project or Team-Based Agile Environment to a Company-Wide Practice

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Agile, Agile Teams, Best Practices

Usually this time of year, the newest State of Agile Report is released from VersionOne (versionone.com) providing data points about the reality of Agile adoption as well as keen insights into what is working, tools in use, demographics, and what barriers continue to exist.

10Dec

The Shift from Data-Centric to Event-Centric Thinking Underscores Digital Business Transformation

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Digital Transformation, Event-Driven Architecture

10Nov

How Technology Re-Shapes Growth & Global Presence in Brazil and LATAM

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Bill Clinton, Brazil, LATAM, LAVCA, StartUps

Every CEO should invest time to share their experience and help the next generation of start-ups grow. As a serial entrepreneur and the founder and CEO of Daitan, I have been part of the global tech transformation for many years, and have always felt it’s important to give back to the growing technology community that has been an important part of my history.

06Sep

An AI-Powered Customer Experience Requires Breaking Down Data Silos

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AI, Architecture, Customer Experience, Data

BLOG - Today’s consumer expectations cannot be ignored. A customer calling a company on their mobile phone, texting via a message window, or emailing to a support system, expects that company to know instantly who they are without asking

11Aug

How Can Artificial Intelligence and Machine Learning Help Us Reimagine the Customer Experience?

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AI, Customer Experience, Digital Transformation, Machine Learning

We hear a great deal about customer-centricity and integrating the customers’ journey at all touch points in order to optimize the customer experience. Considering how customer demands continue to evolve, what does it take for brands to produce a high quality, continuous experience?

11Aug

Practical Facts About the Current State of Machine Learning and Artificial Intelligence

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AI, Data, Digital Transformation, Machine Learning

Over the past 2 years, Daitan has helped a number of our clients implement advanced technology solutions, as well as provided Data Science, Data Engineering, Customer Experience and DevOps resources to successfully implement it. In our experience, companies are taking measured steps to take advantage of Machine Learning and Artificial Intelligence technologies based on clear business objectives that intelligently further growth.

06Aug

How Can Artificial Intelligence and Machine Learning Help Us Reimagine the Customer Experience?

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AI, Chatbot, Customer Experience, Machine Learning

13Jun

How Technology Companies Use Mediated APIs and Microservices to Renovate Monolithic Applications

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APIs, Design & Architecture, Digital Business, Digital Solutions, Digital Transformation, Microservices

The purpose of this post and whitepaper is to present approaches we have successfully deployed on multiple occasions for both mature ISVs and enterprise environments faced with the business imperative to accelerate innovation and leverage their existing assets without disrupting operations of an existing application. In short, we ‘Renovate to Innovate.’

11Jun

Data Science Needs More Than Scientists—It Takes a Team

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Agile, Data Engineer, Data Science, DevOps

Data Science projects are complex and usually result in producing pivotal technology tied to a company’s strategic growth. So, when we build a team, we start with foundational skills like Software Development, Data Engineering and (of course) Data Scientists; and we add DevOps Engineering and Quality Engineering—to ensure the net result is a product the company can use.

11Jun

An AI-Powered Customer Experience Requires Breaking Down Data Silos

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AI, Customer Experience, Data

Today’s consumer expectations cannot be ignored. Gartner predicted that by 2020 customers will manage 85% of their relationship with an enterprise without interacting with a human. The convergence of data, devices and technologies like Artificial Intelligence are making the vision a plausible outcome for businesses pursuing Digital Transformation.

11May

Taking Your Software Code Open Source & How It Changes the Business Focus

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Open Source, Software Development

In the 1990’s the Software industry saw the emergence of Open Source Software (OSS) which became an important part of the total ecosystem, and inspired an awareness of the business value that could come from sharing and the power of community.

11Mar

How Does High Demand for Data Science and Advanced Analytics Skills Create Business Risk?

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Analytics, Business Outcome, Data Science, Hiring

BLOG - Data Scientist is the top job in the USA. And this is the case for a few years in a row according to Glassdoor’s annual report. Demand continues to outpace available resources. A quick search of LinkedIn shows over 11.5K open Data Scientist roles and over 7.4K Data Engineering roles in the USA alone. Incredible.

04Mar

The Shift from Data-Centric to Event-Centric Thinking Underscores Digital Business Transformation

0 Comments
Architecture, Data, Event-Driven Architecture

One of the better outcomes of Digital Business has been that organizations are becoming outward-facing and more inclusive of their customers’ needs, reactions and feedback. As a consequence, their customer facing solutions are transforming into fully inclusive, engagement-driven ecosystems. This shift is driving a transition from retrospective data-centric thinking to event-centric thinking. Gartner comments in their May 2017 report, Champion Event Thinking to Excel at Digital Business:

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