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AI Weekly: Tech, power, and building the Biden administration

November 14, 2020 Big Data

After the defeat of Donald Trump, there was little time between Joe Biden and Kamala Harris’ celebratory speeches and the start of conversations about transition team members and key administration appointments.

Some of the first names to emerge include people with tech backgrounds like former Google CEO Eric Schmidt who may be tapped to lead a tech industry panel in the White House. Since leaving Google, Schmidt extended his services to the Pentagon especially for machine learning. He also acted as head of the Defense Innovation Board at the Pentagon, and the National Security Commission on AI, a group advising Congress that more federal spending is needed to compete with China. NSCAI commissioners have so far recommended things like the creation of a government-run AI university and increasing public-private partnership in the semiconductor industry.

Hearing names like Schmidt and others raised questions about how close the administration will get with Big Tech at a time when tech companies are gaining reputations as the next Big Tobacco. Unlike when Biden first entered the White House in 2009, a number of sources today say Big Tech’s concentration of power is an accelerant of inequality.

A Department of Justice antitrust lawsuit against Google and a congressional committee investigation both found that Big Tech companies enjoy an edge based on compute, machine learning, access to large amounts of personal data, and wealth. The congressional report also concludes that Big Tech poses a threat to competitive free market economy but also democracy.

A paper covered by VentureBeat this week found that a compute divide is driving inequality in AI research, concentrating power, and giving an advantage to universities and Big Tech companies in the age of deep learning. The Biden campaign platform committed to increases in federal research and development spending in areas like AI and 5G up to $ 300 billion, spending that could help address that inequality as well as projects identified by groups like the NSCAI.

The Obama-Biden administration developed a reputation for bringing new concepts into the White House like appointment of a chief technology officer and chief data scientist, support for open access to data, and championing public service by people with tech skills, but that all seems like a long time ago.

Speaking to changing attitudes since then, Tim Wu, who testified as part of a congressional antitrust investigation into Congress, told the Financial Times “There has been a shift since the Obama administration, even among the people working in that administration, in the way they think about power in the tech world.”

Despite those changes, work to build civic tech that improves lives remains undone, said Nicole Wong, who served as deputy White House CTO. She entered the role shortly after the Edward Snowden leaks went public in 2014 and was responsible for privacy, internet, and innovation policy. She was also part of legal teams at Google and Twitter. Wong is now serving on a Biden review team for the National Security Council, according to Reuters.

In a speech delivered about a year ago at Aspen Tech Policy Hub in San Francisco, she said the government has outdated and inefficient tech, and that there’s a pipeline problem for people with tech skills who want to apply their talent to public service. Wong said she still believes that the government can make technology that improves human lives and that it’s important that it do so. Modernizing outdated government tech isn’t moonshot technology, she said, but public trust is at its lowest rate since the 1970s, a trend that started before Trump came into office. That pipeline issue is important because the decline in public trust is due in part to a failure to deliver for the people.

“That’s why the non-glamorous work of modernizing a 70-year-old system matters just as much or more as perfecting a self-driving car, or putting a person on Mars,” she said. “If we can order a gluten-free chocolate cake on our mobile phone while sitting in our living room and have it delivered in an hour then we should be able to help a single mother get food stamps without having to take a day off work and fill out paperwork and stand in line at a limited hours government office. We should be able to get our benefits to our veterans who fought for our country and the world that makes this tech possible.”

Some believe Biden plans to take on Big Tech companies like Facebook. Gene Kimmelman, who testified in favor of antitrust reform last year, will be part of the Department of Justice review team, for example. Others have concluded that initial appointments signal the opposite.

If you’re interested in seeing particulars about some of the tech connections, Protocol made an interactive graph that shows connections between acquaintances, family, and current and former employers. Who the Biden administration chooses may reflect its priorities, the diverse coalition that delivered the Biden ticket to the office, and may inspire people to the kind of public service that Wong talked about in order to solve moonshot problems and improve people’s lives. They can also reflect the shift in attitudes about Big Tech and power that Wu mentioned. The involvement of people like chief of staff Ron Klain seems to indicate they will at least believe in science.

In the days and weeks ahead, we will learn more about what the Biden cabinet and heads of federal agencies will look like. Building the Biden administration will have to take a lot of factors into account, from short term problems like a a global pandemic and urgent need for U.S. economic recovery, but also longer term issues like the decline in public trust in government, concentration of power by Big Tech, the continuing decline of democracy in our time, and the increase of surveillance and autocratic rule at a time of accelerating deployments of AI in business and government.

For AI coverage, send news tips to Khari Johnson, Kyle Wiggers, and Seth Colaner — and be sure to subscribe to the AI Weekly newsletter and bookmark our AI Channel.

Thanks for reading,

Khari Johnson

Senior AI Staff Writer

Best practices for a successful AI Center of Excellence:

A guide for both CoEs and business units Access here

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Building Bridges — Best Practices for BI Teams Working with Data Teams

September 17, 2020 Sisense

Implementing analytics at your company is a multi-team job. In Building Bridges, we focus on helping end-users, app builders, and data experts select and roll out analytics platforms easily and efficiently.

Selecting and implementing a new BI and analytics platform is a big decision and can be a vital part of an organization’s digital transformation. Rolling out a new platform involves everyone who’ll implement, maintain, and most heavily use such a platform.

Advanced analytics and BI democratize access to data, empowering more business users to develop insights, with less reliance on data professionals who have previously been gatekeepers of this information. As business teams become more involved with data in their day-to-day work, it’s natural that they should play a role in choosing the right platform and determining how it will benefit their organization.

Making these decisions — which platform to choose and how to put it into operation— requires buy-in from both the analytics and BI team (the probable end-users/frontline users) and the data team (who will prepare the data, build the models, and connect datasets).

Importantly, to make the best decision for your organization, each team must understand, acknowledge, and address the needs and concerns of the other.

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Working together: Understanding priorities

Mutual understanding can only come about via dialogue between teams, so that they can understand the priorities and needs that their BI and analytics platform should meet. It’s important that the analytics and BI team clearly indicate their needs and that the data team understand what the BI platform will be used for and how they can build the right data model(s) to suit the analytics and BI team’s requirements.

To help achieve this, let’s look at some considerations that data teams and analytics & BI teams should discuss in the vital conversation about selecting and implementing a new platform, so that they both can get the most out of the process.

The five big questions

First, when considering a BI and analytics platform for your organization, there are five big questions that everyone should ask, irrespective of their function. A simple yes or no answer in each case, will help you determine quite simply some fundamental requirements that a platform should fulfil. These five big questions are:

Building Bridges — Best Practices for BI Teams Working with Data Teams

The conversation

Armed with the answers to the five big questions, you’re then in a position to drill down into some details about what a BI and analytics platform should do for you. This is where the really interesting conversation starts, as youestablish where your requirements, questions, and concerns both converge and diverge. We envisage that the conversation could go something like this:

Usability

BI & Analytics Team: Can we find a BI and analytics platform that’s really user-friendly? Can you involve us in choosing something that offers self-service analytics, so we don’t have to hassle you all the time to help us crunch complex data? We’d really like to be part of the selection process.

Data Team: Sure. Let’s work together to find a platform that can meets your needs and ours. From our perspective, we need to be confident that a platform is robust and that it can handle on-premise and cloud data from any source.

While the data team is concerned with storing, connecting, and preparing data for analysis, the BI and analytics team is concerned with examining the data and creating relationships and comparisons between datasets, in order to surface insights and visualize the data. The former are data experts. The latter is more focused on the business needs and usability is a priority for them.

“When we were using a different BI platform, I wouldn’t let frontline business users touch it,” says Jennah Crotts, data analytics manager at Jukin Media. “They’d click one thing, everything would break, and I’d have to rebuild it from scratch. Now, with Sisense, if somebody is up to speed on their data and has gone through some basic training, I can copy a dashboard and give them ownership.”

Governance

BI & Analytics Team: It’s really important that we make our data as accessible as possible to as many users as we can, without unnecessary impediments. Can we make this happen?

Data Team: Certainly, but let’s not forget governance too. It’s also important for us to be able to control access to our data and ensure that proper policies are in place

Data management, including security, is a priority for the data team. Accessibility and the democratization of data are key focuses for the BI and analytics team. To maximize the utility of an analytics platform and the value of data to an organization, data for decision-making should be as accessible and as easy to understand for as many end-users as possible.

Trust and accuracy

BI & Analytics Team: For data, and ultimately insights, to be as accessible as possible, we need analysis and visualizations to be as simple as possible to find and use. Can we ensure that this is possible?

Data Team: We want to make this happen for you, while at the same time ensuring that data isn’t inadvertently mishandled and that problems don’t arise when setting up new KPIs or dashboards. We need to protect the data, the methods of accessing, and the ways it can be analyzed and visualized, while making it as accessible as possible

Both teams are concerned about the quality of the data they’re handling. The BI and analytics team, and end users, want to be sure that they’re receiving and analyzing the most accurate data as possible. However, it’s the data team’s job to manage and prepare the data, and optimize its accuracy, by ensuring it’s “clean”, without errors, duplications and without it being available to unauthorized users. The ability to set access programmatically, by group, team, department, or individual is an important feature that Data teams will look for in a BI platform.

“The benefit to using a BI system,” says Jennah, is that: “Even if you have all of your data mapped beautifully, is: Can you make sense of it? Can you notice trends? Can you identify what’s going on? Having the right BI tool and visualizations can allow you to do a lot of things.”

Scalability, agility, and capacity

BI & Analytics Team: It’s really important that we get the most value we can from a BI and analytics platform. So it shouldn’t just be suitable for now. It must be able to scale with the growth of our business. And scaling up shouldn’t be costly. Positive ROI is essential.

Data Team: Agreed. The platform we choose must be scalable, and agile, to respond to the growth of our business, the increase in the volume of data we’re handling, and changes in our market that require us to pivot. It needs to have the capacity and capability to grow with us.

In the interests of the business, the BI and analytics team seeks to maximize ROI, which is why ensuring that a BI and analytics platform is future-proofed so that it can scale up with the growth of the organization and the data it generates. The data team is solely focused on the capability of the platform to scale up and its capacity to handle increased volumes of data.

“To test the agility of the platform, I was able to connect the technical person at Sisense with our guy in engineering,” Jennah says. “This was helpful because if you try to reword what your tech guy is saying, it just won’t make sense. So when the right technical people can speak directly to each other, it helps the flow of the setup enormously.”

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Cost-effectiveness

BI & Analytics Team: On the subject of ROI, a BI and analytics platform has to be cost-effective. It needs to save users time and resources while improving performance, and decision-making. We need to be sure we can achieve these aims, so we should conduct a proof of concept before making a final decision.

Data Team: Indeed. We appreciate that we can’t implement a complex platform just for complexity’s sake. It has to serve our business, our needs, and our objectives. And it has to address the particular challenges that any business has. A POC is essential.

When it comes to cost-effectiveness, the teams align. Both need to ensure that their choice of BI and analytics platform can deliver what it promises, what each of them requires and the maximum benefits to their organization, with no hidden or unexpected costs.

Versatility

BI & Analytics team: Please keep people — the users — in mind. We really need to put end-users first vs focusing mainly on IT needs. Any platform that we choose must be able to solve a range of different data-related issues, each of which affects different people in different functions within the business.

Data team: We actually think that our objectives meet here. Our platform of choice must be able to handle the widest variety of data from the widest variety of sources, precisely to maximize accessibility and usability. More and more data is unstructured (text, video, audio, graphical data and the like) and comes from non-technical sources. It requires technology like NLP to deliver usable findings for all. We want to reduce the time it takes to clean, integrate, and maintain data.

So, for instance, the C-Level wants to see high-level performance reports across departments. Mid-level executives want to make better decisions in their line of business. All data, and all types of data, must be accessible to all, subject to governance and policies. This necessitates that a BI and analytics platform be as versatile as possible.

“We’re starting to get more and more positive feedback from our C-level executives,” Jennah reports. “They’re saying things like, ‘This is a lot cleaner looking.’ ‘You were able to make those changes a lot quicker than I’m used to.’ ‘You’re able to get this to me faster.’ and stuff like that.”

Speed

BI & Analytics team: We’re missing opportunities when we can’t get insights quickly. We need data and visualizations in real time so we can make decisions and pivot fast.

Data team: We get it. Speed and ease of use are critical, but so is thoroughness. We must be sure that we choose a platform that handles and manages all our data properly so you can be confident that you’re getting the best and most accurate insights.

In a world where data is generated by the second, quickly getting your BI and analytics up and running could give you a competitive advantage. More importantly, making data-driven real-time decisions can mean the difference between success and failure, so from a business perspective, speed and ease of use are imperative. They should not be impeded by the need for accurate data management and preparation, which advanced BI and analytics should be capable of achieving equally quickly.

“The head of our content acquisition team, a major data consumer, was unsure about our switch. She was worried about transition costs and maintaining access to her particular data requirements.” Jennah says. “But when I showed her the first Sisense dashboard on a remote screen-share and was able to edit the dashboard to her specifications in real-time, she lost her mind over the speed and ease of use of the new platform.”

Implementation

BI & Analytics Team: How are we going to implement a new platform? We want results quickly so we can make decisions fast and get changes under way.

Data Team: Let’s not rush this. We’ll do our due diligence with a POC and ensure the right platform meets our needs, then consider how best to implement a new platform within the organization. If we get it right the first time, it’ll be easier, quicker, and more cost-effective in the long term. Tell us what you need and that will dictate timing.

Implementation can happen incrementally by department, company-wide in one sweep, limited to certain levels within an organization, and it’s important to decide whether to include embedded analytics and white-labeling for new revenue opportunities. All of these considerations will influence how quickly a new platform can be implemented.

“There’s been solid social interaction with the right kind of people who understand what they’re doing. Our sales guy did his homework and came back and hit every single request with full beautiful explanations,” says Jennah. “That allowed me to go to leadership and say they’re definitely getting a POC because they hit all the boxes. Because when the VP of engineering gets on the phone and starts asking the questions, they need to be able to answer them.”

Cloud, on-premises, or hybrid?

BI & Analytics Team: We need to have the fastest, most flexible, and most scalable access to data of any kind and in any form, to benefit as much as possible from the information we generate and handle. The Cloud has the capacity and flexibility that legacy on-premises solutions lack. Plus, cloud solutions include support, maintenance, and upgrades, which is cost-effective.

Data Team: Sure. We just need to consider whether we put all of our BI and analytics on the cloud, run it on-premises, or have a hybrid of the two? And how do we handle legacy systems on-premises? Is it more cost-effective and efficient to migrate them to the cloud, or maintain them on-premises alongside cloud analytics for newer data?

This is a key consideration when seeking to maximize the capabilities of BI and analytics and future-proofing them. The future of data and analytics is in the cloud. Its capacity is almost unlimited. You only pay for the capacity and processing power you need. There’s no need to invest in your own IT servers or additional data center facilities or hire a team to manage and maintain the application. The cloud services vendor will do all of that for you. And implementation is immediate, with no lead time need for ordering, installation, or deployment.

“I was really interested in a cloud-based interface.” Jennah reports. “I didn’t want a situation I had with another platform where I was constantly downloading and uploading data to communicate with internal business users. Other platforms that are so reliant on Internet speed won’t cut it in our current situation. It’s faster for me to build reports from scratch in Sisense than it would be to edit them in another platform.”

The first step to data-driven success

Choosing and implementing the right BI and analytics platform is a major project that can be hugely valuable for your organization. It will enable you to maximize the value you get from your data and will optimize the insights you can take from it. Plus, done right, it will empower many more of your colleagues to engage with data, and make vital decisions. Asking these questions and having this conversation, can be the first, essential step in establishing a successful, data-driven future that can supercharge your organization.

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Adam Murray began his career in corporate communications and PR in London and New York before moving to Tel Aviv. He’s spent the last ten years working with tech companies like Amdocs, Gilat Satellite Systems, and Allot Communications. He holds a Ph.D. in English Literature. When he’s not spending time with his wife and son, he’s preoccupied with his beloved football team, Tottenham Hotspur.

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Can a Microsoft Dynamics 365 User Save Money by Building Their Own Reports?

September 15, 2020 CRM News and Info

Companies evaluating Microsoft Dynamics 365 Sales will often ask us, “Can Microsoft Dynamics 365 users build their own reports?”

The answer comes down to a couple of factors:

What kind of reports do you need?
What kind of relevant experience does your team have?

By building their own reports, a business could potentially save thousands of dollars. However, there is a lot to consider.

First things first: What kind of reports do I need?

This is often the main source of confusion. What one person considers a report may just be a list for another. When asking your CRM partner for a report, there may some misunderstanding as to what constitutes a report.

Here are three common substitutions to consider instead of a full-blown report:

CRM Views: Views in Dynamics 365 Sales are essentially a filtered list based on certain criteria put in place by the user. For many clients, this is enough on its own. Moreover, once a user learns how to create their own CRM views, it helps them become autonomous. This helps speed up the analysis process for this user or department.
Dashboards: Dashboards display critical data that you need to review on a regular basis from your CRM (customer relationship management) tool. Potentially, much of the data you would need in a report can be viewed from a dashboard, which you can create yourself within Microsoft Dynamics 365 Sales. Key statistics can be displayed as graphics or lists depending on user preferences and requirements. Like Views, this is something that users can create themselves with a quick training, some understanding of the fields within the forms, and a vision of what they would like to review.
Excel templates: As a final option we would suggest looking into Excel templates in the CRM. This allows you to build your spreadsheets as you would like them to be presented and refresh the data as you need it. The most common application for this tool is to share information with your clients. What differentiates this from a report is the limitations in filtering and intelligence (e.g.: display this information if “x” exists). For some applications it makes more sense to create a report rather than an Excel template.

By using these tools to their full potential, you can probably limit the number of reports you need and save the extra costs associated with building them. The first step is then to ask yourself if you really need the information to be consumed as a report or if one of these tools can meet your needs.

In some cases, reports are necessary as there are limitations to what you can do in a view. If this is the case for you, you likely want to know if you can build these reports yourself and what the cost will be.

Next step: Can my team create their own reports in-house?

The short answer is it depends. Creating your own reports depends on the relative competency levels available internally. Ask yourself if anyone on your team has the SQL/Fetch XML experience required to build reports.

For those who want to create their own reports but don’t have the experience, it might be worth considering Microsoft Power BI instead. This business intelligence solution is more dynamic and simpler to use once the data set is created and in place.

You could improve your skills by taking classes and consulting a partner. But realistically, the cost of these could come out to about the same as having your reports developed by a Microsoft Dynamics partner.

Bottom line: Can I build my own reports or not?

The answer is not the same for everyone. Building your own reports may sound appealing, but unless you have the competencies required internally, you may have to look at alternatives, like Power BI, CRM views or dashboards, and Excel templates. It basically boils down to what kind of report you need and how much experience your team has.

Our suggestion would be to have an honest and open discussion with your Microsoft Dynamics partner to ask them what building a specific report entails. Don’t be afraid to ask questions to see if there is a better way of doing things. This way the partner will get a clearer idea of what you need, and the effort required to produce it.

Here at JOVACO Solutions, we have decades of experience working with organizations to help them get the information they need. Our consultants are available to figure out the best way for you to take advantage of the wealth of data stored in your system. Contact us today to tell us more about your challenges and objectives.

By JOVACO Solutions, Microsoft Dynamics 365 specialist in Quebec

About JOVACO Solutions

JOVACO Solutions is a leading ERP and CRM solution provider operating in Quebec for over 35 years. As a specialist of Microsoft Dynamics business management solutions, we offer a wide range of products and services to meet all the needs of professional services firms and project-based organizations. We also offer specialized project management tools and timesheet add-ons fully integrated to Microsoft Dynamics solutions. Visit our website or contact us for more information.

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Monitoring the Power Platform: Custom Connectors – Building an Application Insights Connector

June 28, 2020 Microsoft Dynamics CRM

Summary

Connectors are used throughout Power Platform Pillars such as Microsoft Power Automate and Microsoft Power Apps. They are also used in Azure services such as Azure Logic Apps. Connectors are a wrapper around first and third party APIs to provide a way for services to talk to each other. They represent the glue between services, allowing users to setup Connections to connect various accounts together. These connectors encompass a wide range of SaaS providers including Dynamics 365, Office 365, Dropbox, Salesforce and more.

This article will demonstrate how to build a custom connector for use with Power Automate and Power Apps Canvas Apps. This custom connector will attempt to build a connection to Azure Application Insights to assist Makers with sending messages during run time. We will discuss building and deploying an Azure Function and how to construct a Custom Connector. Finally we will discuss testing and supplying run time data from Power Automate.

Overview of Azure Function

Azure Functions provide a great way to build micro services including ones to help surface run time data from Power Automate Flow or Model Driven Application Plug-in tracing. Azure Functions can be written using .NET Core and included is native integration with Azure Application Insights. Alternatively, we can import the Azure Application Insights SDK to provide a streamlined approach to delivering messages. This article will focus on using the HTTP entry point and Azure Application Insights SDK to deliver messages to Application Insights.

Overview of Custom Connectors

Custom Connectors allow developers to supply custom actions and triggers that can be used by Microsoft Power Automate and Microsoft Power Apps. These connectors provide a reusable no or low code approach to integrating with an Application Programmable Interface otherwise known as an API. The complexity of interacting and implementing a connection and call to the API is hidden from makers, allowing focus on finding a solution to whatever business objective is at hand.

The custom connector can be thought of as a solution to a no cliffs approach to empowering makers. If a connector doesn’t exist for your particular need, for instance an in house API, a custom connector can be used to bridge the gap. No longer are we having to build and send HTTP requests or manage connection flows as the connector will fill the gap.

For additional information, including considerations for Solution Aware Custom Connectors allowing for migration between environments, refer to the article Monitoring the Power Platform: Connectors, Connections and Data Loss Prevention Policies.

Overview of the Open API Specification

Open API is a specification built on the desire and need to standardize how we describe API endpoints. Built from Swagger, the Open API dictates how an API should be used. Everything from security to required fields are detailed allowing integrators to focus on developing and not chasing down API specs. One great feature is the ability to design a specification first without relying on code being written. This allows Makers to define what they are looking for with Custom Connectors.

This specification is used by Power Platform Custom Connectors to build out the various triggers and actions that will be made available. This will be covered in more detail in the Building a Custom Connector section.

For more information regarding Open API please refer to this reference from Swagger.

Building the Azure Function

The section below will document the steps I took to create the Azure Application Insights Azure Function. There are several ways to build, frameworks to use, additional requirements to adhere to, etc that are not represented here. That said these steps should allow developers to create a proof of concept that can be used to learn and build from.

Creating the Visual Studio Project and Gathering Dependencies

To build the Azure Function, I started with Visual Studio 2019 and created a new Azure Function project.

AUTHOR NOTE: CLICK EACH IMAGE TO ENLARGE FOR DETAIL