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Tag Archives: Things

Learn Things So You Can Build Things — A Data Analyst’s Opinion

December 6, 2020   BI News and Info
pexels negative space 169573 2 Learn Things So You Can Build Things — A Data Analyst’s Opinion

This blog post is guest written by Tomi Mester of data36.com. 

When it comes to data science, it’s not about what you learn. It’s about what you are able to build with what you’ve learned.

The field of data science has been growing rapidly—especially in the last few years. We see exciting new tools and methods emerge all the time. And while these can be great, I feel that these can cause some confusion as well. Why? Because they make data professionals think about the wrong questions.

Asking the wrong questions

What do I mean by asking the wrong questions?

Examples of wrong questions might be:

  • What are the coolest new tools to try out?
  • What are the most exciting data science problems nowadays?
  • How can we fit these into our business (to experiment with them)?

Instead, we want to ask better questions like:

  • What business problems (or opportunities) do we have right now?
  • How can data help with this?
  • Why and how will our data project be useful for the company?
  • What should I learn to start building it?

Within data science, there is enormous hype around new tools every time a new machine learning algorithm is released. Or a new cloud-based solution is available. Or a new module is implemented for this or that programming language. And so on.

But aren’t these new tools important? Well, yes, but…

Tools are important, but with a caveat

Let’s think about an example from cook. You can’t cook soup without a spoon. But when eating the soup, very few people will say: “Hmmm, you have a pretty nice wooden spoon.” Instead, most of them will say: “Yum, this food tastes really good!”

And that’s because, at the end of the day, tools are just tools. You have to learn how to use them…

But that’s not the full sentence. It’s rather:

You have to learn how to use them so you can build useful things with them…

And that’s still not quite all.

You have to learn how to use them so you can build useful things with them that will have a positive impact on your business’s bottom line.

Maybe it sounds obvious written down. And if it is for you, that’s great. But I see many data professionals choose to focus on fancy data science solutions over the data science solutions they actually need. And then they hit a wall.

Unpopular opinion: most data scientists won’t need to know anything about deep learning

Let me give you just one example: deep learning.

I run a data science blog where I publish tutorials for aspiring data scientists on topics like the basics of Python or the basics of SQL, and so on.

And I get this question every week from someone: “When will you publish a tutorial on deep learning?”

And the answer is always the same: never.

Okay, I have to admit, I played around with the idea to quickly draft an introductory article on the topic… But it was tempting only for one reason: I know I’d get a lot of clicks for that article.

Most people want to learn about deep learning only because it’s popular. Why is it popular? Because it’s used for cool stuff, like self-driving cars at Tesla—and for that reason it gets a huge amount of media attention. That makes people excited and suddenly everyone wants to apply deep learning in their own projects.

But (at least in my opinion) it doesn’t work that way! A data science project should always start by defining the problem you want to solve. And once you have that, then you can choose the best tool to get the job done!

The naked reality is that in, most data science projects, there is a much higher demand for more traditional tools, like:

  • descriptive analytics and reporting
  • data cleaning and data wrangling
  • automating your processes
  • simple predictions and forecasting
  • simple classification methods

I know, at first, these sound less cool than deep learning… But believe me, when you are working on a real project, they are just as exciting (if not more)! Why? Because they get you useful information a lot more quickly than building trying to tackle a project with something complicated like deep learning. 

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Why we can’t have nice things

August 22, 2020   Big Data
 Why we can’t have nice things

Automation and Jobs

Read our latest special issue.

Open Now

If you spend your professional life worrying about security, it can get a little disconcerting when you see that some enterprises have a tough time managing even base levels of security. What’s worse is that the challenge just got more complicated. As Satya Nadella recently said, COVID-19 has truncated the two years of digital transformation into two months, and that holds true for security considerations too.

With the sudden shift brought on by COVID-19, teams have embraced the economic benefits of the cloud to solve many issues. But every rose has its thorn, and along with the great benefits of cloud migration, companies have also adopted the new security concerns that come with it, and many are wholly unprepared.

A recent analysis of 2 million scans of 300,000 public cloud assets running on Amazon Web Services (AWS), Microsoft Azure, and Google Cloud Platform (GCP) revealed more than 80% of organizations have at least one neglected, internet-facing workload that is either running on an unsupported operating system or has remained unpatched for more than 180 days. The report also found that 60% of organizations have at least one neglected internet-facing workload that it is no longer provided with security updates. Any of these issues in an organization should merit immediate patching; however this rarely happens.

There are many reasons, especially in the current climate, why these security lapses remain unresolved within enterprises. Many organizations in the time of COVID-19 are dealing with budget cuts, and for many, teams are being consolidated and reorganized. While these cuts are understandable, given an average cost of $ 4.77 million per data breach, DBAs, developers, and security teams need to rise above and be more careful with their new tools.

Your cloud database services vendor is not your mother

Recently, I attended a virtual conference session on database security considerations when migrating workloads to the cloud.” An attendee asked the question, “What can I do to ensure a cloud vendor can secure my company’s sensitive data?” And, rightfully, the speaker replied, “It’s not the cloud vendor’s responsibility to ensure your security controls are being extended to cloud environments; it’s yours.”

As is the case with any service provider, the company will do its best to ensure there are no flaws in their overall systems to allow a breach, but your organization’s data within the cloud instance is your responsibility. Think of it like a storage unit. The unit provider provides you with the storage locker itself and will ensure the locker is up to standards, sometimes even providing some basic perimeter security. But you are responsible for buying your own lock and ensuring the security of your unit. If you decide not to lock it, don’t be surprised if people access your locker and steal your property. It’s a common and dangerous misconception that the cloud vendor has visibility and oversight over how your sensitive data is being protected. It’s not the cloud vendor’s responsibility to provide it. They provided you with the service, but security is on you.

Your security teams don’t know what they don’t know

Oftentimes, even when a company acknowledges its security responsibility, the unfortunate reality is that internal miscommunication is almost as big a problem as misunderstanding the service provider’s responsibility towards your data. The developers and DBAs that migrated and configured the system are responsible for the service-level of the database or application itself, not the security of the data within. They believe the security teams are entirely responsible for data security, virtually absolving themselves of many responsibilities in that area. Meanwhile, many times the security teams were never even informed of the new service the developer used, yet are somehow expected to secure it. All the while, this cloud-based environment may well be exposing sensitive data and be susceptible to breaches.

Be your organization’s security conscience

If you are waiting for your cloud vendor to be a true collaborative partner on security issues, or for your developers to suddenly develop strong security wherewithal, you have a long wait ahead of you. Cloud environments can be a huge boon for companies looking to reduce budgets, however with timetables for cloud migrations being shortened and new systems being added more rapidly, the process is not always handled responsibly. Databases present a target-rich environment and are being unnecessarily exposed to enterprising hackers. Companies need to rein in the process to ensure proper security.

It’s true that maintaining security is a challenge, but it’s not impossible. Clear communication between security teams and the DBA and application owners and clear understanding of the delegation of responsibilities are a major first step and will prevent security best practices from falling by the wayside. Now is the time to take a security inventory, because ultimately it does not matter how strong your perimeter security is or how much money you save migrating to the cloud if you’re exposing your valuable data.

Ron Bennatan is the founder and CTO of jSonar and is an expert on data security, having worked in the industry for over 25 years at companies such as J.P. Morgan, Merrill Lynch, Intel, IBM, and AT&T Bell Labs. He was co-founder and CTO at Guardium, which was acquired by IBM where he later served as a Distinguished Engineer and the CTO for Data Security and Governance. He has a Ph.D. in Computer Science and has authored 11 technical books.

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3 Powerful Things Real Companies Did With Microsoft Dynamics 365

August 14, 2020   CRM News and Info
crmnav 3 Powerful Things Real Companies Did With Microsoft Dynamics 365

What are the results? You can read hundreds of articles about the features of Microsoft Dynamics 365, but it is the actual results that matter.

Instead of just sharing overviews and hypothetical scenarios, we want to share some recent real-world examples of business challenges the Crowe team solved for clients, across industry and business function, with the Microsoft Dynamics 365 platform.

  1. Implemented an incident management system with the ability to send communication alerts to maintenance and operations staff in Microsoft Dynamics 365 for a Public Transit Authority.
    1. Developed a streamlined approach for managing incidents, events and routing to the appropriate department.
    2. Automated alerts send messages real-time to maintenance and operations staff regarding active incidents.
    3. Integrated with a content management system to automate population of forms and submitting documentation.
  1. Implemented a system to manage the assignment and tracking of contact tracers across the State in Microsoft Dynamics 365 for a State Public Health Agency.
    1. Transformed a complex multi-tabbed worksheet that contains data from multiple sources into a single system that allows for efficient scheduling of resources.
    2. Managed the eligibility and training of contact tracers in order or to identify available and qualified resources to deploy across the state.
    3. Automated the notification process to inform contract tracers of required training and assignments.
  1. Implemented ZoomInfo integration to automate updates to contacts in Microsoft Dynamics 365 for a Professional Services Firm.
    1. Provided process to “clean” existing database of 350k contacts every month instead of once per year and confirmed new contacts entered are accurate and enriched with data for immediate data enhancement.
    2. Improved Marketing and Sales productivity with higher-quality, readily-available leads and ability to reach new target segments.
    3. Reduced speed to market by decreasing manual labor and data entry while increasing trust in CRM as an accurate data source.

What does your business want to accomplish?

The Crowe CRM team has decades of combined CRM solutions experience and a track record of project success. We’ve got the mindset and methodology needed to design, deliver, and implement effective CRM solutions.

We want to help your company do powerful things with Microsoft Dynamics 365. Contact our team to start the discussion at crminfo@crowe.com or 877-600-2253

By Ryan Plourde, Crowe, a Microsoft Dynamics 365 Gold Partner www.CroweCRM.com

Follow us on Twitter: @CroweCRM

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Project Manager Benefits – 5 Things

May 27, 2020   Microsoft Dynamics CRM

Save Thousands of Dollars by Bringing on a Project Manager

Some may say paying to have a Project Manager is too costly, but I will be discussing 5 benefits of having a Project Manager to help manage your further project and how the benefits outweigh the cost.

5 Advantages of a Project Manager

Know What You Are Paying For and Save Thousands

Down below are some benefits that Project manager brings to a project:

1) Scheduling: our project managers have access to their entire teams’ schedules and can coordinate and schedule meetings as needed. By having this to coordinate with multiple parties it saves lots of time. When trying to coordinate with multiple parties, days or weeks can go by before a time is locked in. For you having to be the scheduler for meetings, the project manager can split that time in half.

2) Budget: amongst many of project managers main jobs is to monitor and hold the project team to stay within the budget for that specific project. With having to deal with project architects and developers, as much as they try to stay under budget, more often than not they go over budget because it’s not their main job to worry about the budget but to do their jobs. Having a Project Manager to help monitor that budget will help your team prioritize and maximize their time  so they don’t waste time. On projects without a project manager, teams often find going over budget as they don’t monitor the hours because of times spent on tasks.

3) Scope: one of many other key aspects to a project managers job is to monitor and manage the scope of the project. While working on projects it can be super easy to fall into a process where developers and other leads allow scope creep and modifications to the project that are outside of the scope. This leads to an additional budget that was not expected, and timelines that are longer than anticipated. The project manager can help make sure that scope creep will not  affect major deadlines and priorities.

4) Risks & Issues: a major reason many like to have a project manager on their projects is to help deal with any potential risks and or issues that could come up. Having someone or something that can assess those risks, what they may do or cost to the project and help identify the best way to assess those risks is a key factor to project success. A project manager helps manage those risks so they don’t affect your deadlines. Many times these risks postpone deadlines because there isn’t one resource dedicated to tackling these obstacles.

5) Efficiency & Direction: project managers directly work with the project team to assess tasks, and ensure that those tasks are taking the project down the right road. Most times without a project manager, tasks are identified too early or aren’t relevant for the immediate needs of the project. With project managers this efficiency can be avoided.

xProject Manager 625x415.jpg.pagespeed.ic.BeyrlZZEe  Project Manager Benefits – 5 Things

As you can see all 5 of these key points are beneficial to having a project manager. More often than not the time project manager cost is added into a quote and contract so you know what you are paying for. Although having to pay for a project manager is another cost for a project, you will save thousands of dollars by bringing on a project manager to help use your time and budget efficiently.

As a Microsoft US Partner of the Year and Inc. Magazine’s Best Places to Work winner, JourneyTEAM helps your organization with the right guidance and technologies for you. Contact us.


Article by: Dave Bollard – Head of Marketing | 801-436-6636

JourneyTEAM is an award-winning consulting firm with proven technology and measurable results. They take Microsoft products; Dynamics 365, SharePoint intranet, Office 365, Azure, CRM, GP, NAV, SL, AX, and modify them to work for you. The team has expert level, Microsoft Gold certified consultants that dive deep into the dynamics of your organization and solve complex issues. They have solutions for sales, marketing, productivity, collaboration, analytics, accounting, security and more. www.journeyteam.com

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4 Things You Need to Know for Successful Enterprise CRM Integration

May 4, 2020   CRM News and Info

The enterprise IT environment is complex. Many systems, technologies and practices that were developed at various times coexist in the same world. With expectations for technological advancements at their peak, we’re tasked with enabling these systems to work together harmoniously to support the continuous sharing of information.

Systems and data must connect to allow full use of capabilities as if all information were native to each. There also must be many ways to present information to end users, though data is evolving on a constant basis. Given this complexity, it’s not surprising that an intelligent CRM system in an enterprise environment requires specialized insight and know-how to ensure a seamless integration that’s both relevant and current.

What does an enterprise intelligent CRM solution look like? Any smart solution first and foremost must be designed as an enterprise-first application: one that is flexible, scalable, upgradable and ultimately easily deployable.

To a great extent, success in the enterprise environment depends on the use of “enterprise literate technology,” as opposed to reliance on “technology literate enterprise” concepts that were common in the past.

Enterprise literate technology understands an organization’s business needs and is built with the standards of what the company needs to accomplish in mind. It can help predict outcomes, better facilitate operations, and even automate day-to-day tasks. With today’s functional and technical complexity, heterogeneous integration requirements, and need for scale and security, CRM integration success depends on an enterprise literate technology approach.

From an enterprise management standpoint, the first task is to find a platform designed for this purpose. The following four considerations are critical when sourcing intelligent CRM software for enterprise systems.

1. Flexibility and Context Matter

Enterprise CRM solutions should be tailored to meet business specific needs. The primary goal for any CRM solution should be a seamless user experience, delivered through a fully integrated single application that is responsive across all devices and platforms.

A good choice will offer a comprehensive customer view by integrating enterprise and third-party data sources through a customized, context-aware system. Systems like this automatically manage all communication and context passing between the CRM system and other third-party portlets needed to ensure everything works together as a single integrated system.

What’s more, enterprise intelligent CRM with built-in artificial intelligence has the ability to incorporate additional data sources to allow users to leverage available information effectively in order to better service customers.

From automating workflows to eliminating burdensome administrative tasks, the flexibility of an intelligent enterprise solution provides a deeper understanding of the customer, which helps with decision-making processes and simplifies day-to-day operations.

2. Is It Scalable?

CRM is more than just a software. It’s an essential strategic growth tool that all enterprises need. One of the main motivators for any enterprise CRM provider should be to equip an organization with the simple tools needed in the early stages of a business, as well as the capabilities to scale up as the business expands and grows.

Implementing a reliable, fully scalable CRM system in the beginning as part of an overarching business strategy ensures seamless growth down the road. After all, a good foundation — which includes a company’s ability to scale up to meet the demands of growth and challenges as they arise — is fundamental to any organization’s success.

With an enterprise-first approach to CRM, organizations can rest assured that the simple coordination of all the different customer touchpoints in a business — from ales and marketing to face-to-face interactions with customers — will be facilitated effectively through one centralized platform as the business grows.

This is what makes ongoing collaboration, information sharing and task management simple and efficient. Keep in mind all of this must be done with a robust and complex security system, too. A truly scalable solution allows organizations to configure security to protect their customers and match their requirements as the business expands, while allowing information to be shared across the company dependably.

3. What are the Integration Capabilities? Is It Upgradable?

When CRM integration is an afterthought, failure is inevitable. Instead, the technology must allow for integration with a wide variety of client platforms, data sources and applications, since every organization has different needs.

Without integration for items such as social media and news feeds, for instance, it is next to impossible to take customer management and experience to the next level. For organizations and CRM solutions alike, a comprehensive understanding based on the client’s complete relationship with the company is essential for customers to receive the expected level of personalized, continuously evolving service.

Look for and integrate a system that understands the nature and concerns of enterprise operations — including its ability to upgrade as needed. Technical and functional challenges are to be expected, but a well-integrated system supports upgradability from the beginning.

Among other things, it is important to not force unnecessary data replication or compromises on data security, visibility and residency. Instead, organizations should deploy an enterprise-first way of thinking that provides configurable, world-class functionality along with the business controls needed to take operations to the next level.

4. Deployment Should Be Simple

A purpose-built enterprise CRM software system should make deployment simple. It should be compatible with a variety of open source and common software platforms. An intelligent platform takes the “how”out of the equation by translating processes easily. It should be easy to tailor it to specific business needs.

The user’s job should be simply to dictate what the system should do, not how it will be done. Both the functional and technical complexity should be handled by the software itself, which should be sophisticated enough to render information-sharing appropriately across all common Web applications and technology devices.

Easy deployment insulates a software investment from the shifting underlying technology landscape, and ultimately makes the development and maintenance of a CRM solution more manageable over time.

There is unmatchable value in deploying an enterprise CRM system that can be customized for an organization’s specific business needs to give the ROI and improved customer experience companies seek.

Integrating an enterprise intelligent CRM system can seem daunting, but it doesn’t have to be. Every business has a unique set of needs, and selecting robust software that allows for thoughtful integration of data and applications can improve operations and help businesses expand and grow, while making the transition seamless and mitigating unnecessary stress.
end enn 4 Things You Need to Know for Successful Enterprise CRM Integration


Adam%20Edmonds 4 Things You Need to Know for Successful Enterprise CRM Integration
Adam Edmonds is VP of products at
NexJ Systems, which specialiazes in CRM products for global financial services institutions. With almost two decades of experience developing customer management solutions in financial services and insurance, Edmonds is responsible for establishing overall product vision and designing easy-to-use solutions that solve financial advisors’ problems.

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Things to do at home 4

April 7, 2020   Humor

4. Make silly videos about the pandemic

And with lots of time on their hands, they made another one. If you have not had enough of the Sound of Pandemic, watch on!

One last thing, I was hoping that people would send me more things like this to post for everyone’s enjoyment. Send me videos, photos… heck, I figured out a hack to get videos out of Facebook, so send me even those!

 If you liked this, you might also like these related posts:
  1. Home, Sweet Home
  2. McCain claims he is not a rich man – is that why he is selling his home?
  3. If you lived here, you’d be home!
  4. Old Soldier’s Home
  5. Hammering Home

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Things to do at home 2

April 6, 2020   Humor

2. Climb Mt Everest.

https://www.bbc.com/news/av/uk-52165949/man-climbs-height-of-everest-on-his-staircase

 If you liked this, you might also like these related posts:
  1. Home, Sweet Home
  2. McCain claims he is not a rich man – is that why he is selling his home?
  3. Palin’s home town disadvantage
  4. Old Soldier’s Home
  5. If you lived here, you’d be home!

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A Patchwork of Useful Things

April 5, 2020   CRM News and Info

Adobe just announced what it calls the first
digital economy index. It seems like it’s modeled after other indices usually kept by the federal government to measure economic output and consumption. The Adobe index captures only consumer consumption behavior though.

Some of its insights include new shopping behavior, such as which products have become hot items or decreased in popularity over time. For instance, we’re buying more groceries online — 8 percent now versus 6 percent in 2014, which seems like the base year. Also, computer purchases now make up just 8 percent of the shopping basket, down from 21 percent in the wake of mobile computing. Not exactly news.

Something called “digital purchasing power” is up 20 percent over 2014, meaning you can get more shopping online than elsewhere. I get that, but it’s likely only bait. When the switch is made or shipping becomes unfree, we might see different numbers.

There’s more, and it’s worth evaluating the index for several reasons. Certainly the digital economy is here and not likely to go away until something better, faster and cheaper comes along in about 50 years — and that’s the point.

The entire digital revolution has done many things, and one of its most pronounced accomplishments has been the continuous hollowing out of the economy, also known as “commoditization.”

Today, thanks to digital supply chains, you can build anywhere at the lowest costs and buy everywhere at whatever the market will bear — good things, except when they are not. For instance, try buying commodity surgical gloves, face masks and other PPE items, and you discover how democratically the shortages are shared.

At the end of the day, this index is interesting and useful, even if it shows only what’s missing. That would be much more information about manufacturing and production and raw material costs — in other words, the supply side of all the consumption the index measures.

Tech Community Philanthropy

I recently wrote about Zoho’s noble effort to help support its customers and small, medium, and even large businesses by making its technology available to them at no charge. Zoho is providing technology that helps people work from home in two programs:
Remotely, a virtual productivity platform comprising 11 collaboration applications for business; and the Emergency Subscription Assistance Program (ESAP).

Those are good things, and it takes nothing away from those efforts to note that they don’t do much for workers in the trades, bartenders and waitstaff, store clerks, and many others whose jobs mandate working with customers.

Luckily, the US$ 2 trillion relief package signed last week will help some of them, but even that won’t do the whole job. That’s OK though, since what’s happening is that the private and public sectors are cobbling together a patchwork of overlapping solutions that will get the job done. There will be more.

Salesforce Takes Long View

Here’s a quick look at what Salesforce is doing in this regard.

The company has made a concerted effort over the years to position itself as a philanthropist, an enterprise that does good while doing well. Baked into its DNA is the 1,1,1 model of donating 1 percent of its equity/profits, employee time and product to help the community.

The model was so successful that CEO Marc Benioff and others founded
Pledge One Percent to help other like-minded companies build their own philanthropic efforts. It’s nice to report that thousands of companies of all sizes have taken the pledge too.

For the coronavirus crisis, Salesforce is extending its efforts in multiple ways through charitable giving, and donating products to people who may need cloud apps to get through. Some of the high points:

  • Tableau (a Salesforce company) has delivered a
    free Coronavirus Data Resource Hub — a collection of visualizations, curated data sources and prebuilt dashboards to help people better understand the potential impacts of the virus on their organizations. A lot of CDC data is presented in clear and informative ways here.

    If you get a chance, check this out. It provides both American and global perspectives on things like virus spread, which you’ve likely seen, but it also tracks things like mobility, to give a sense of how stationary we have become or not, which could be a leading indicator of where the virus might crop up in a couple of weeks.

  • Quip is being offered for free to any Salesforce customer or nonprofit organization to help remote teams across the globe collaborate and remain productive while working from home. Quip is a multi-user document management system that helps groups work together remotely.
  • A
    publicly available Trailmix on Trailhead provides tips on how to work from home and maintain personal well being during this time.

Salesforce also is upping its philanthropic donations to address the outbreak:

Making the Rounds

As you might know, I appear as a commenter from time to time on the Gillmor Gang, a streaming show that discusses timely topics in tech, entertainment and the economy. The show is hosted by Steve Gillmor, formerly of TechCrunch and currently a VP at Salesforce.

Steve’s wife Tina produces the show, and I usually trade ideas with Steve, venture capitalist Keith Tear, former Apple executive Michael Markman, and television industry executive, businessman and author Frank Radice. Mostly I listen, because you can learn a lot from these people.

I never know what we’re going to talk about, but last weekend we got to speculating about how working at home will change American industry. It’s right in line with this continuing piece.

We know that there are many jobs that won’t change or will change little, but there are many knowledge jobs that have the potential to change plenty. Certainly the availability of all sorts of cloud solutions will give people and their companies the opportunity to experiment with different styles of working.

So maybe offering to let the public use cloud apps free is one of those philanthropic ideas that might show real returns down the road, in the same way that online conferencing apps sparked a renaissance in the tech sector after the dot-com bubble burst.

It’s hard to say for now, but the one thing that I think is apparent is that the universe is conducting a natural experiment on all of us.

My Two Bits

These are tough times from multiple perspectives. With some essentials like medical protective gear in short supply, you might conclude — erroneously — that no donations are useful.

That ignores the good that can be done through food donations, establishing safe places to sleep and take a shower, and many other things that only you might think of. Donating to local hospitals is never a bad idea.

If your company is doing something to help out during this crisis, no matter how small, let me know at
Denis@BeagleResearch.com. Remember, we’re making a patchwork, so every contribution is important. I’d love to learn about your efforts and possibly pass on your good ideas.
end enn A Patchwork of Useful Things

The opinions expressed in this article are those of the author and do not necessarily reflect the views of ECT News Network.


Denis%20Pombriant A Patchwork of Useful Things
Denis Pombriant is a well-known CRM industry analyst, strategist, writer and speaker. His new book, You Can’t Buy Customer Loyalty, But You Can Earn It, is now available on Amazon. His 2015 book, Solve for the Customer, is also available there.
Email Denis.

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5 Things to Know About Event-Driven APIs and Apache Kafka

October 10, 2019   TIBCO Spotfire
EventDrivenAPIsTIBCO 1 696x464 5 Things to Know About Event Driven APIs and Apache Kafka

APIs are becoming the crux of any digital business today. They provide a multitude of internal and external uses, including making B2B connections and linking building blocks for low-code application development and event-driven thinking. Digital business can’t exist without event-driven thinking. There are real benefits to developing event-driven apps and architecture—to provide a more responsive and scalable customer experience.

Your digital business requires new thinking. New tools are required to adopt event-driven architecture. This includes being able to implement tools such as Kafka, Project Flogo®, and event-driven APIs. That said, if you’re not adopting event-driven APIs, you’re leaving revenue, innovation, and customer engagement opportunities on the table. 

Here are five things to know about how Kafka and event-driven APIs that can benefit your business.

Offer a wide range of benefits and use cases for businesses

When it comes to the implementation of event-driven architecture, specifically, event-driven APIs, there are a number of benefits for digital businesses. Event-driven APIs are able to deliver real-time responsiveness, support microservices for optimal agility, and enable scalability. Additionally, Kafka provides the processing of high-speed event streams, which can invoke event-driven APIs and services. This allows for a number of business use cases in a wide variety of industries such as telecom, financial services, and travel. Examples of specific use cases include creating personalized offers, developing scalable engagement, and supporting the customer journey. 

Combat roadblocks that are commonly found in adopting an event-driven architecture

With the development of event-driven architecture, developers and businesses face a number of roadblocks. A few common roadblocks are:

  • The need for service execution and iteration to be loosely coupled from one another to deliver more agility
  • A way to manage interactions between events and microservices
  • A standard specification for communication

Luckily, event-driven APIs help combat these roadblocks. The interoperability between loosely coupled services, microgateways for protection and mediation between events and microservices, and a defacto standard make event-driven APIs attractive to developers.

Made possible by the rapid adoption of cloud 

The rapid adoption and use of cloud have made event-driven architecture and tools more widely available, as a managed service and in public or private clouds. This has allowed developers to work across their systems in multiple programming languages, leverage microservices, access multiple databases, and to deploy as a function-as-a-service (FaaS). 

Can be built with the help of an open-source framework

Developers are turning to a more open-source offering to build successful event-driven architecture and APIs. Apache Kafka is an open-source event stream-processing platform with the goal to provide a highly scalable platform for handling real-time data feeds. TIBCO provides enterprise support for Kafka via TIBCO® Messaging. A tool such as Flogo can be leveraged for event-driven application development as it’s lighter than Java or Node.js, supports an event-driven microgateway, can be deployed as a serverless function, via containers, or edge IoT, and offers machine learning capabilities. Alternatively, AsyncAPI offers an open-source API specification which has become the defacto standard for event-driven APIs. It also supports event-driven microservices, IoT, and streaming APIs. 

Scalable to increase the volume, velocity, and variety of data for decision-making

One of the major trends when it comes to data usage and consumption is the increase in volume, velocity, and variety of data used for decision-making. This is reflected in a paradigm shift for developers, embracing new event-driven architecture, specifically event-driven APIs, at scale. What’s more, is that Kafka plays a key role as a hyper-scale, high-speed processor of streaming event data. Developers are now able to handle large volumes of streaming events with ease. 

We’ve worked with developer-focused analyst firm Redmonk to better explain the challenges, opportunities, and tools available to adopt and event-driven architecture, including Kafka and event-driven APIs. Watch the webinar to learn why more and more developers are turning to event-driven APIs.

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Artificial stupidity: ‘Move slow and fix things’ could be the mantra AI needs

October 6, 2019   Big Data

“Let’s not use society as a test-bed for technologies that we’re not sure yet how they’re going to change society,” warned Carly Kind, director at the Ada Lovelace Institute, an artificial intelligence (AI) research body based in the U.K. “Let’s try to think through some of these issues — move slower and fix things, rather than move fast and break things.”

Kind was speaking as part of a recent panel discussion at Digital Frontrunners, a conference in Copenhagen that focused on the impact of AI and other next-gen technologies on society.

The “move fast and break things” ethos embodied by Facebook’s rise to internet dominance is one that has been borrowed by many a Silicon Valley startup: develop and swiftly ship an MVP (minimal viable product), iterate, learn from mistakes, and repeat. These principles are relatively harmless when it comes to developing a photo-sharing app, social network, or mobile messaging service, but in the 15 years since Facebook came to the fore, the technology industry has evolved into a very different beast. Large-scale data breaches are a near-daily occurrence, data-harvesting on an industrial level is threatening democracies, and artificial intelligence (AI) is now permeating just about every facet of society — often to humans’ chagrin.

Although Facebook officially ditched its “move fast and break things” mantra five years ago, it seems that the crux of many of today’s technology problems come down to the fact that companies have moved (and continue to move) too fast — “full-steam ahead, and to hell with the consequences.”

‘Artificial stupidity’

 Artificial stupidity: ‘Move slow and fix things’ could be the mantra AI needs

Above: 3D rendering of robots speaking no evil, hearing no evil, seeing no evil.

Image Credit: Getty Images / Westend61

This week, news emerged that Congress has been investigating how facial recognition technology is being used by the military in the U.S. and abroad, noting that the technology is just not accurate enough yet.

“The operational benefits of facial recognition technology for the warfighter are promising,” a letter from Congress read. “However, overreliance on this emerging technology could also have disastrous consequences if faulty or inaccurate facial scans result in the inadvertent targeting of civilians or the compromise of mission requirements.”

The letter went on to note that the “accuracy rates for images depicting black and female subjects were consistently lower than for those of white and male subjects.”

While there are countless other examples of how far AI still has to go in terms of addressing biases in the algorithms, the broader issue at play here is that AI just isn’t good or trustworthy enough across the spectrum.

“Everyone wants to be at the cutting edge, or the bleeding edge — from universities, to companies, to government,” said Dr. Kristinn R. Thórisson, an AI researcher and founder of the Icelandic Institute for Intelligent Machines, speaking in the same panel discussion as Carly Kind. “And they think artificial intelligence is the next [big] thing. But we’re actually in the age of artificial stupidity.”

Thórisson is a leading proponent of what is known as artificial general intelligence (AGI), which is concerned with integrating disparate systems to create a more complex AI with humanlike attributes, such as self-learning, reasoning, and planning. Depending on who you ask, AGI is coming in 5 years, it’s a long way off, or it’s never happening — Thórisson, however, evidently does believe that AGI will happen one day. When that will be, he is not so sure — but what he is sure of is that today’s machines are not as smart as some may think.

“You use the word ‘understanding’ a lot when you’re talking about AI, and it used to be that people put ‘understanding’ in quotation marks when they talked about it in the context of AI,” Thórisson said. “When it comes down to it, these machines don’t really understand anything, and that’s the problem.”

For all the positive spins on how amazing AI now is in terms of trumping humans at poker, AlphaGo, or Honor of Kings, there are numerous examples of AI fails in the wild. By most accounts, driverless cars are nearly ready for prime time, but there is other evidence to suggest that there are still some obstacles to overcome before they can be left to their own devices.

For instance, news emerged this week that regulators are investigating Tesla’s recently launched automated Smart Summon feature, which allows drivers to remotely beckon their car inside a parking lot. In the wake of the feature’s official rollout last week, a number of users posted videos online showing crashes, near-crashes, and a general comical state of affairs.

So, @elonmusk – My first test of Smart Summon didn’t go so well. @Tesla #Tesla #Model3 pic.twitter.com/yC1oBWdq1I

— Roddie Hasan – راضي (@eiddor) September 28, 2019

This isn’t to pour scorn on the huge advances that have been made by autonomous carmakers, but it shows that the fierce battle to bring self-driving vehicles to market can sometimes lead to half-baked products that perhaps aren’t quite ready for public consumption.

Crossroads

The growing tension — between consumers, corporations, governments, and academia — around the impact of AI technology on society is palpable. With the tech industry prizing innovation and speed over iterative testing at a slower pace, there is a danger of things getting out of hand — the quest to “be first,” or to secure lucrative contracts and keep shareholders happy, might just be too alluring.

All the big companies, from Facebook, Amazon, and Google through to Apple, Microsoft, and Uber, are competing on multiple business fronts, with AI a common thread permeating it all. There has been a concerted push to vacuum up all the best AI talent, either through acquiring startups or simply hiring the top minds from the best universities. And then there is the issue of securing big-name clients with big dollars to spend — Amazon and Microsoft are currently locking horns to win a $ 10 billion Pentagon contract for delivering AI and cloud services.

In the midst of all this, tech firms are facing increasing pressure over their provision of facial recognition services (FRS) to the government and law enforcement. Back in January, a coalition of more than 85 advocacy groups penned an open letter to Google, Microsoft, and Amazon, urging them to cease selling facial recognition software to authorities — before it’s too late.

“Companies can’t continue to pretend that the ‘break then fix’ approach works,” said Nicole Ozer, technology and civil liberties director for the American Civil Liberties Union (ACLU) of California. “History has clearly taught us that the government will exploit technologies like face surveillance to target communities of color, religious minorities, and immigrants. We are at a crossroads with face surveillance, and the choices made by these companies now will determine whether the next generation will have to fear being tracked by the government for attending a protest, going to their place of worship, or simply living their lives.”

Then in April, two dozen AI researchers working across the technology and academia sphere called on Amazon specifically to stop selling its Rekognition facial recognition software to law enforcement agencies. The crux of the problem, according to the researchers, was that there isn’t sufficient regulation to control how the technology is used.

Above: An illustration shows Amazon Rekognition’s support for detecting faces in crowds.

Image Credit: Amazon

“We call on Amazon to stop selling Rekognition to law enforcement as legislation and safeguards to prevent misuse are not in place,” it said. “There are no laws or required standards to ensure that Rekognition is used in a manner that does not infringe on civil liberties.”

However, Amazon later went on record to say that it would serve any federal government with facial recognition technology — so long as it’s legal.

These controversies are not limited to the U.S. either — it’s a global problem that countries and companies everywhere are having to tackle. London’s King’s Cross railway station hit the headlines in August when it was found to have deployed facial recognition technology in CCTV security cameras, leading to questions not only around ethics, but also legality. A separate report published also discovered that local police had submitted photos of seven people for use in conjunction with King’s Cross’s facial recognition system, in a deal that was not disclosed until yesterday.

All these examples serve to feed the argument that AI development is outpacing society’s ability to put adequate checks and balances in place.

Pushback

Digital technology has often moved too fast for regulation or external oversight to keep up, but we’re now starting to see major regulatory pushbacks — particularly relating to data privacy. The California Consumer Privacy Act (CCPA), which is due to take effect on Jan 1, 2020, is designed to enhance privacy rights of consumers living across the state, while Europe is also currently weighing a new ePrivacy Regulation, which covers an individual’s right to privacy regarding electronic communications.

But the biggest regulatory advance in recent times has been Europe’s General Data Protection Regulation (GDPR), which stipulates all manner of rules around how companies should manage and protect their customers’ data. Huge fines await any company that contravenes GDPR, as Google found out earlier this year when it was hit with a €50 million ($ 57 million) fine by French data privacy body CNIL for “lack of transparency” over how it personalized ads. Elsewhere, British Airways (BA) and hotel giant Marriott were slapped with $ 230 million and $ 123 million fines respectively over gargantuan data breaches. Such fines may serve as incentives for companies to better manage data in the future, but in some respects the regulations we’re starting to see now are too little too late — the privacy ship has sailed.

“Rolling back is a really difficult thing to do — we’ve seen it around the whole data protection field of regulation, where technology moves much faster than regulation can move,” Kind said. “All these companies went ahead and started doing all these practices; now we have things like the GDPR trying to pull some of that back, and it’s very difficult.”

From looking back at the past 15 years or so, a time during which cloud computing and ubiquitous computing have taken hold, there are perhaps lessons to be learned in terms of how society proceeds with AI research, development, and deployment.

“Let’s slow things down a bit before we roll out some of this stuff, so that we do actually understand the societal impacts before we forge ahead,” Kind continued. “I think what’s at stake is so vast.”

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