Externally, data can be used to better market to customers, keep track of their spending habits, understand their pain points, and gain insight into their purchasing decisions. Internally, data can be used to improve processes, cut through overhead, spur productivity, and make decisions.

It all comes down to business intelligence, which encompasses all of the things that leaders take into account in order to make decisions about their organizations. However, data has allowed leaders greater insight into the reality behind these decisions, where for many years these leaders relied on smaller data sets and gut feelings.

Digital transformation has become a favorite phrase in the lexicon of business strategy over the past several years. At the heart of digital transformation is data and analytics. Gathering data about various aspects of the organization, analyzing that data to find trends, and understanding those trends to create business intelligence to help make decisions.

How do technology managers realize the benefits of data and analytics? On the whole, by implementing sensors and software that gathers information, and utilizing an analytics platform to parse through that information to recognize trends. All of this is available to companies right now. However, different businesses and different environments will require different solutions. There is no one-size-fits-all solution to data and analytics. Instead, building an analytics strategy is about figuring out what’s possible and customizing it to your organization.

Let’s look at what’s possible, and what others are doing as part of their digital transformation strategies in terms of data and analytics.

Meeting Rooms

The meeting space has become a great starting point for organizations implementing a strategy around data and analytics. Meeting rooms are isolated, relatively uniform, and a huge part of the productivity of an organization’s staff. It makes sense that organizations want to use data and analytics to streamline the meeting space as much as possible.

Room occupancy sensors can be installed to understand when and how many people participate in different meetings. This information can be gathered to provide an overhead view of how meeting spaces are being utilized in your office. Perhaps the meeting space on the third floor is seldom used. The meeting space on the second floor is used often, but only at 50% capacity. Huddle spaces on the other hand are being utilized throughout the day.

The specific technology within the meeting rooms can be connected to control platforms to gather data as well. How often are screens used? What about audio equipment? Are people actually utilizing the touch capabilities of the screen? What kind of devices are being brought into the room? How often are different products breaking? How much time does the IT team spend fixing these problems?

Air quality sensors also bring in information. Are meeting spaces too hot or too cold? Is there too much carbon monoxide in the room, making employees unhealthy?

You begin to make decisions. That third-floor space can be converted into huddle spaces. The second-floor space can be divided into two meeting rooms. People love the touchscreens, so we should bring in more of those. People also like to use their own devices, so we should enable them to easily connect to displays in the room. This product from this manufacturer breaks down too often – let’s not use them anymore.

The secondary benefits in meeting rooms are great as well. If you learn that most meeting rooms aren’t being utilized after 4:00, you can automate those rooms to shut down hours earlier than before. This saves on utility costs. If a room is too hot or too cold you can regulate that and make the office more comfortable for employees.

None of this information is possible to gather without data and analytics – unless you want to hire full time employees to sit in meeting rooms and write everything down.

Manufacturing Floor

Being in the pharmaceutical industry, data is extremely important in both ensuring that the yield is at maximum capacity (and therefore maximum profit), and that the process and yield meet strict FDA requirements. Analytics have allowed both companies to better monitor and better create manufactured products.

In 2016, TechDecisions was able to speak at length with Gloria Gadea-Lopez about how Shire has utilized Dell Statistica in its process. Gloria works as the Director of Manufacturing Systems in Internal manufacturing at a facility that manufactures only about 30 batches of its product per year, so every batch is extremely important to the overall profitability of the company. More importantly, these batches will be used to combat real life diseases, so the pressure to make sure that there are no anomalies and all of the batches are delivered is serious.

“My joke is, we don’t have big data, we have wide data,” says Robert Dimitri, Associate Director Manufacturing Systems at Shire. “Meaning we’re lucky if we manufacture 30 batches in a year. Our processes run for weeks and months. So we have to collect an enormous number of variables in order to monitor our process. We need to enable the end users on the data side with us much data as possible because that’s all we have. With the length of time that our processes run we have to be aware of what’s going on and able to react to anything that’s happening during the manufacturing process. Having that visibility is absolutely critical.”

There was once a time when scientists at the facility would hand-record data samples and enter them into spreadsheets for analysis. This took time, as data could only be obtained by checking sensors manually, and in many cases by manually taking samples and recording the data. By adding sensors and tying them into a data collection platform, Shire was able to save time and effort, and collect data sets at a much faster rate – days and weeks which used to take weeks and months.

Statistica then analyzes those data sets to provide information about how the manufacturing processes are performing. This analysis can happen for processes that are daily as well as those that take months to run their course. Data scientists within the manufacturing facility can then take the analysis and use the information to better run their processes. So, for example, analysis might recognize that yield is greatest when a batch has a certain pH level at a certain temperature. Scientists can then monitor the pH level and temperature to ensure greatest yield. And this happens in almost real-time, so that scientists don’t have to wait until the batch is finished to understand how well the batch will come out. They can monitor as it goes in order to create the best yield for every batch.

Statistica also allows Shire to scale and validate data. “Things happen in an environment of constant change. So maintaining compliance while operating in constant change is challenging,” says Gadea-Lopez. “So we need to have the right application that allows us to manage change. At the same time, continuing the expansion of these applications, either by onboarding new products and processes, or by expanding the use of the core application to new areas of use.

“One area that’s very interesting right now is that the facility in Lexington utilizes disposable technology. Traditionally, we make the product using stainless steel [reusable technology]. Single-use systems are a completely different way of manufacturing. We have another plant that makes the same product on the traditional stainless-steel technology. So we can monitor performance, get approval for the facility, and demonstrate parallels. That’s where these applications are priceless – we can monitor and use all of the data from the separate systems at the same time.”

This same process can be applied to any manufacturing facility – implement sensors, gather data in real time, and ensure that manufacturing is at peak performance.

Shipping and Receiving

The transportation industry has also seen huge benefits from implementing data and analytics in order to better track and prepare for shipping and receiving. This involves GPS sensors in vehicles moving products and materials around, and scanning those shipments as they arrive and depart.

This allows organizations real-time understanding of potential delays in shipments. When an accident causes a truck to sit still for two hours, the organization is aware of this delay. They can reach out to customers to warn them – some platforms even have the capability to automate this and let customers know about delays quickly so those customers can better prepare for a delayed shipment.

As this data is gathered, organizations can find patterns for better efficiency. Perhaps, with all of the miles racked up, it is better to switch to electric vehicles and save on gasoline. Maybe there are shipments that can be slightly delayed in order to place them on the same vehicle. Perhaps certain drivers aren’t performing as well as others. Maybe certain vehicles are breaking down more often than others.

Data and analytics gives you this insight before it becomes a problem. It offers real-time updates to shipping and receiving. The faster you get shipments where they are going, the more revenue you can generate. The more efficiently you can get shipments to where they are going, the more money you save.

Retail Environments

Retail environments have also become great entryways into data and analytics strategies.

Again, people counting sensors can give you an idea of how many people are in stores and where they congregate. Facial recognition software can give you an idea of where people of specific genders or ages move throughout the store. This can help organizations better set up the store, to ensure the right products are in the right spots.

Inventory management is also a huge opportunity for data and analytics. The faster organizations understand what products are flying off the shelves, and what products are gathering dust, the faster they can update their strategies. Cancel a shipment of the underperforming products and use that money to purchase more of the best-selling product.

Data and analytics in a retail environment can help organizations better understand how customers shop – which allows organizations to better suit their stores toward customer habits.

Your Organization

Again, data and analytics aren’t one-size-fits-all. You’ll need to tailor your strategy toward your information.

The most important parts are the sensors that gather the data you need, and the analytics platform that digests that data and provides charts, graphs, and spreadsheets for your leaders to easily interpret.

Keep that in mind, and you’ll be well on the way to digital transformation.

The post How to Use Data and Analytics to Make Business Decisions appeared first on My TechDecisions.

Data like productivity, meeting room utilization, IT infrastructure performance, ticket response time and security analytics can help set the organization up for future success, but it takes a lot of careful and particular planning – as well as technology – to gather that data in the first place.

Why should we collect data?

Understanding what your organization needs, the ability to be agile and respond to changing dynamics is now more important than ever, says Patrick Hubbard, head geek at IT software company SolarWinds.

“For example, hybrid operations are often the result of organizations adopting cloud, SaaS, HCI, and more to solve specific business challenges, not infrastructure technology limitations,” Hubbard says.

“To provide leadership with analytics they expect, IT teams are increasingly collecting and analyzing non-infrastructure data in combination with traditional performance metrics.”

In online retailing, data like shopping cart abandon rate, total checkout ASP and last-minute upsell CTA performance would be valuable metrics and help measure responsiveness, resulting in faster browsing results, reducing errors and keeping customers shopping with you.

In online retailing, data like shopping cart abandon rate, total checkout ASP and last-minute upsell CTA performance would be valuable metrics and help measure responsiveness, resulting in faster browsing results, reducing errors and keeping customers shopping with you.

“It’s in effect transforming customers into performance monitoring agents to ensure the delivery of high-visibility services and quickly spot issues with their underlying resources,” Hubbard says.

In another industry like healthcare, comparative analytics of mobile hardware AP connection density wit patient occupancy data would be valuable.

Along with assuring that wireless equipment is functioning as intended, teams can use the data to optimize their APs and distribution networks.

“And in most cases, IT pros are finding business operations data is easier to integrate in the past,” Hubbard says. “Though this shouldn’t be a surprise—IT pros are great at finding ways to get the data they need.”

What kind of data should we be collecting?

Collecting data from every corner of each of the organization’s IT systems may seem like the right approach since in theory you should be able to learn more with that amount of information, but that can be more trouble than it’s worth, Hubbard says.

“But in reality, too much data can be worse than too little data,” Hubbard says. “If you need a data lake for operations metrics, it can distract the team from what really matters—managing and transforming the critical systems of the business.”

A better approach, Hubbard says, is to use your monitoring and management tools to measure, then assign value to operations data.

“Observability and visibility are really about zooming back your monitoring perspective to consider new or more helpful instrumentation,” Hubbard says.

“With that in hand, select the most valuable subset of all available data that best measures IT and infrastructure operations relative to the needs of the business.”

That’s a different approach from simply connected to monitoring interfaces and collecting data from every application, server and network report.

“It’s an ongoing re-evaluation of what to monitor, what data to keep, where blind spots are, and what detail the team needs for reconfiguration, optimization, and troubleshooting,” Hubbard says.

Data collections systems: three primary options

According to Hubbard, there are three main options for data collection solutions: single vendor tools associated with products, free or in-house developed technology and third-party commercial solutions.

Although there are three options, most IT pros end up adopting third-party tools because they tend to aggregate most data in one system.

“This in turn allows multi-source data analysis in an increasingly decentralized environment,” Hubbard says. “It also reduces time spent building and managing data collection platforms themselves.”

There are a variety of options available, ranging from on-premise to hosted solutions; agent or agentless based collection; network, app, or cloud focus; and self or vendor-managed installations.

“As is the software industries habit, solutions are offered to fill just about every nook, cranny, and team requirements’ profile,” Hubbard says. “It’s a golden age for data collection, and IT pros have more and better options than ever before.”

Deploying data gathering infrastructure

IT pros can deploy data collection gathering infrastructure in two plans, each with different options, according to Hubbard.

First is the storage and analysis plane that acts as a central collector, data analyzer, dashboard and report server. Some can be self-hosted, typically running alongside other business applications on virtual servers.

Others are software-as-a-service based, that shift the platform management and hosting outside.

“IT pros generally select the back-end option based on licensing and appetite for making data collection WAN dependent,” Hubbard says.

There’s also the polling or agent plane that connects to infrastructure, apps, APIs and other custom data sources. Components include network monitors, remote collectors, cloud-native app integration agents, log aggregators, traffic analyzers, SIEM and policy analysis, backup monitoring, multipath network analysis and more.

“This plane is also rapidly expanding to include services like Salesforce, Office 365 and Google Workspace, marketing and production applications, and more,” Hubbard says.

Typically as an add-on service from the cloud, organizations can also opt to augment their data practice with artificial intelligence and machine learning.

“These systems make the value of all the collected data more easily accessible to less-technical business experts and are focused more about discovery and insight than specific data point collection or reporting,” Hubbard says, citing Microsoft Power BI as an example.

Data collection and a digital transformation is not as technical as you might think

Effective digital transformation is actually less about budget and technology and more about process and habits, says Hubbard.

“With digital transformation, it can be difficult to measure the actual ROI of modernization, migration, or new development despite dozens of online vendor post-transformation calculators,” Hubbard says. “The only thing that matters in transformation is your business, your data, and your processes.”

Read Next: Database Software That’s Great for SMBs

Existing monitoring systems can observe newly transformed operations and compare them with performance, costs and user satisfaction before, during and after that digital transformation takes place.

“Reassuring the C-suite that you’ll maintain visibility even during big-budget, high-visibility transformation projects can go a long way to reducing risk anxiety and solidifying resolve to make complex changes,” Hubbard says.

“Better, expanded performance collection can also prove transformed applications are achieving the business goals driving the technology change in the first place.”

The post How IT Pros Can Collect Data to Improve Business Operations appeared first on My TechDecisions.

That’s just what happens on screen. The most powerful systems of today will further remote management to include monitoring and control of devices – choose which screens are on or off, and be notified when there is a problem with a display or device. This kind of automation not only delivers the right message at the right time, but can save money in utility costs.

One of the biggest draws of modern digital signage systems is in data and analytics. Today’s systems can gather information about who is watching what, when, analyze that information, and visualize it to provide owners of the systems with business intelligence to better understand how to change or expand on systems.

Click here to register for this webinar on September 23rd at 2:00 PM ET

With quality information, you understand what your customers need and how to create the kind of great experiences that build loyalty.

During this webinar presented by Commercial Integrator, TechDecisions, AVI-SPL, and Samsung, you’ll learn about the innovative ways digital signage is being used to connect with external audiences while providing your team with valuable performance data.

We’ll also introduce you to Samsung’s MagicINFO, a comprehensive management solution for data-driven marketing. MagicINFO makes it easy for businesses to create, schedule, and deliver dynamic content while empowering them with the insight they need to:

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Join us on Sept. 23 at 2 p.m. EDT and learn how to go from raw data to information that is ready to be viewed by your audience, while giving you a dashboard with detailed reports so you can gauge the impact of your content.

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The post Webinar: Content, Device, and Data: Expect More from Your Digital Signage appeared first on My TechDecisions.

In the healthcare industry, this practice is nothing new. Doctors often use data analysis to track diseases and better understand risks and results from different procedures. So it’s no surprise that in the battle against the COVID-19 pandemic, the United States is turning to data mining to help better understand how the disease spreads, affects different people, and more.

In an exclusive from The Daily Beast, we’ve learned that Palantir, a data-mining firm created by Pete Thiel that has worked with a number of government agencies in the past, will play a significant role in gathering and analyzing data about COVID-19 for the United States.

According to The Daily Beast, Palantir will provide a major aspect of the analytics platform called HHS Protect Now that the federal government is underway creating. The company has signed a contract with the Department of Health and Human Services to bring added expertise to the program.

According to The Daily Beast:

The HHS Protect Now platform, which is set to be unveiled later this week, pulls data from across the federal government, state and local governments, healthcare facilities, and colleges, to help administration officials determine how to “mitigate and prevent spread” of the coronavirus, according to a spokesperson for the department.

The White House will receive nightly briefings on the analysis of the data collected as part of HHS Protect Now.

This project really highlights the value of gathering and analyzing data. At this point many pieces of technology on the AV side as well as the IT side are connected to the network. If they’re connected, then they can be outfitted with sensors that send valuable data to an analytics platform.

That platform then gives insight into a number of business aspects. From how long rooms are being utilized, to how much energy is being consumed (and paid for), to different levels on manufacturing processes in real time. The possibilities are limitless, and can be catered directly to your organization.

If it’s good enough to help fight a global pandemic, then its good enough to help you make better decisions in your organization. Every technology manager should think about data analytics and how they could fit for you.

The post Data-Mining Company Palantir Will Gather COVID-19 Data for U.S. appeared first on My TechDecisions.

The tech giant controls over 60 percent of browsers, runs code on about 85 percent of sites on the internet, and is inside about 94 percent of apps. In short, it’s everywhere, collecting data on users’ searches. Even though it collects such data, Google claims to not sell it; instead, it makes its money through real-time bidding.

Real-Time Bidding

This process occurs when publishers “auction off ad space” via their apps and websites, the Electronic Frontier Foundation reports. Here, users’ sensitive data is shared with numerous other adtech companies. The data then moves through other layers, including: supply-side platforms, which collect users’ data to sell; ad exchanges, which organize auctions between them and advertisers; and demand-side platforms, which “bid” on behalf of advertisers and decide which ads to show.

Google has some form on control at all levels of real-time bidding, which brings in money for the tech giant. For example, through a user’s browser, Google and can share data with an advertiser through “cookie matching,” enabling third-party companies to connect their own cookies to Google’s. From here, advertisers end up sending Google money as it sends that data into the ecosystem, the Electronic Frontier Foundation says.

This exchange, among other branches of real-time bidding, bypasses obtaining users’ consent to access their data. “It is at the center of everything that’s wrong with privacy in tech.”

Real-Time Problems

The Electronic Frontiers Foundation says that one of the only ways customers can better protect their data and make it more challenging for Google to rake in money is for stronger consumer data privacy laws. For example, it points to the California Consumer Privacy Act (CCPA), which went into effect at the start of 2020, and enables users to opt out of having their data collected and sold. Business that don’t follow the law can be fined, among other penalties.

However, the foundation states that privacy laws, especially those similar to the CCPA, need to be more stringent; people’s right to privacy should be a priority, instead of something off of which to make a profit. “On its own, the CCPA is not enough to fix the problems with tech’s use of personal data, but it is a good first step down the road to privacy reform… [it] underscores the need for a more comprehensive law that treats privacy as a default, not an option.”

The post This is How Google Really Makes Its Money appeared first on My TechDecisions.

Do you know when their meeting rooms are being used? Do they know how many people are in them when they are used?

We spoke with Warren Fernandez at Microsoft to learn more.

MyTechDecisions: What are the benefits of gathering data in meeting rooms?

Warren Fernandez: Imagine if your meeting room could be more than just a static place to facilitate work? When we think about smart spaces, we’re not constrained to focus only on the physical room itself, we actually take a people-centric approach and think about both the people who use the space and the people who own the space.

What sort of meeting room data should be collected in these kinds of spaces?

WF: The actual data can vary, but generally, you want to start with a minimal set of key measurements which inform the way a space owner or operator can maximize productivity of room users. Temperature, lighting, air quality, whether or not there’s someone in the room and how many are, etc. It all has to be done securely, too, while protecting privacy.

Learn More: Preparing Your Meeting Rooms for Teams: A Free Webinar

How can decision-makers make better choices about meeting rooms?

WF: There’s some obvious cost saving opportunities to, say, tying a room’s temperature data into a building’s HVAC system. But utilities are the tip of the iceberg. Typically, the most expensive asset in a room is the people inside it. So any action an operator can take to improve how efficient the people in the room can become will pay dividends in the long run.

For example, having the ability to detect when CO2 levels in a room are rising – something that can reduce productivity in humans – and being able to send an automated command to an HVAC system to increase airflow to that room.

Or, having the ability to know that a room that’s designed and budgeted for up to 20 people at a time but ultimately learning it is only used by a maximum of only 7 people presenting an opportunity to subdivide.

For more information, visit the Teams Devices Marketplace.

The post Why You Should Collect Meeting Space Data (And What to Do With It) appeared first on My TechDecisions.

The Office of the Australia Information Commissioner (OAIC) is taking Facebook to federal court, “alleging the company committed serious and/or repeated interferences” with Australia Facebook users’ privacy.

Australia’s suit claims that that personal data from Facebook users was disclosed to the This is Your Digital Life app, which was built by developer GSR, “for a purpose other than that for which is was collected.” The suit alleges that the app was used by Cambridge Analytica “to obtain and process Facebook users’ data for political ad targeting purposes,” TechCrunch reports.

Most importantly, the suit explains that the people who are most affected by the app are the “Facebook friends” of those users: “Facebook disclosed personal information of the Affected Australian Individuals. Most of those individuals did not install the “This is Your Digital Life” App; their Facebook friends did,” the OAIC said in a statement. “What is known, is that Facebook disclosed the Affected Australian Individuals’ personal information to the “This is Your Digital Life” App, whose developers sold personal information obtained using the app to the political consulting firm Cambridge Analytica, in breach of Facebook’s policies. As a result, the Affected Australian Individuals’ personal information was exposed to the risk of disclosure, monetisation and use for political profiling purposes.”

If Australia wins in court, Facebook could be looking at up to $529 billion in fines. This sum is based upon the logistics of Australia’s Privacy Act: there is a civil penalty of up to $1.7 million “to be levied per contravention,” TechCrunch says. In the Cambridge Analytica case, Australia’s watchdog believes that 311,074 users were affected among the millions of other profiles lifted in the scandal. As a result, “the potential fine here is circa $529BN.”

In a statement to TechCrunch, Facebook said that it has been working with the OAIC and has made changes to its platform to “restrict the information available to app developers.” It also said that it has implemented “new governance protocols” and is building new controls to better protect users.

The post What Decision Makers Need to Know About Australia’s Lawsuit Against Facebook appeared first on My TechDecisions.

Although the penalty isn’t yet finalized, it would be one of the largest proposed by the Federal Communications Commission in decades, and the first action taken on the issue of customers’ location data being sold. The four wireless carriers will be given the opportunity to respond and argue against the fines, the New York Times says.

The Federal Communications Commission will fine the carrier based on the number of days their customers’ data was sold. Senator Ron Wyden of Oregon, one of the first to raise major issues with data sharing, called the fines “comically inadequate” to deter companies from repeating these offenses.

Who Cares if They Know Where I Am?

Selling customers’ location data is a particularly big deal because it can potentially put users’ safety and privacy at risk; anyone who has a mobile device is at risk. But, for carriers, customers’ location data has always been a goldmine: “it was consistently available and included almost every American with a mobile phone. Carriers sold access to it for marketing purposes and services like bank fraud protection, under contracts that required location companies to get customers’ consent,” The New York Times says.

The telecommunications industry is supposed to be “subject to more stringer laws” to protect users’ privacy, but that hasn’t always been the case. Companies have not always followed the contracts made with customers, and had little way of enforcing them, which enabled customers’ personal data to be open and fair game for usage; this includes law enforcement officials obtaining and using data to go after persons of interest. As a result, the Federal Communications Commission found that major wireless carriers had broken federal law “by being negligent” with users’ data.

It will be interesting to see how AT&T, Sprint, T-Mobile, and Verizon react if the $200 million in fines is enacted. Will it be enough to tighten their methods of securing users’ data? Or will it be a slap on the wrist, provoking them to making money off of their users without users’ knowledge? Then, there are the users – will they snap to attention and take their business elsewhere to a more safety-conscious carrier? Or will they stay with a carrier that may have betrayed their privacy? Only time –and fines – will tell.

The post 4 Wireless Carriers Might be Fined Millions for Selling Customers’ Location Data appeared first on My TechDecisions.

Organizations can use the data from their access control system to determine if an employee or contractor is displaying abnormal behavior, according to the company.

Symmetry Business Intelligence analyzes how a person’s access activity is tracked and establishes patterns based on a risk score methodology. For a example, anomalous behavior may raise a person’s score, while high-risk identities are flagged in a dashboard.

Read Next: New Viking Electronics Panic Button Allows Security to Silently Monitor or Engage

Dashboards within Symmetry Business Intelligence provide the security team with an at-a-glance look at identities with the highest risk scores. Scores are generated based on the reader location, time of day and a user’s access patterns.

Symmetry Business Intelligence is said to help easily identify employees, contractors and other identities that may pose the highest risk to a company.

Keeping in line with AMAG’s commitment to providing open solutions, Symmetry Business Intelligence has been designed from the ground up to easily integrate with other systems, according to the company.

Over the past five years, AMAG has released Symmetry CONNECT identity management, Symmetry GUEST visitor management and Symmetry incident management, all open, Cloud-based security systems designed to provide more flexibility and options for the end-user.

This article first appeared on My TechDecisions’ sister site Security Sales & Integration.

The post AMAG Adds Analytics Engine to Line of Enterprise, Cloud Solutions appeared first on My TechDecisions.

Over the past few years, Google has been able to “infiltrate more than half of the nation’s primary and secondary schools by offering a ‘free’ web-based service.” Kids are able to access applications, such as email, through that service, which allegedly enables the tech giant to monitor them. For example, Google Education is used by more than 80 million educators and students; more than 25 million teachers and student use Chromebooks, too.

Additionally, the lawsuit alleges that Google “misled” schools and parents that there were no issues around privacy with its educational solutions, and alleges that parental consent was not gained to data-mine their children. “The company’s data-mining of kids violates the Children’s Online Privacy Protection Act, which requires companies to get a parent’s consent before collecting the name, contact information and other personal details from a child under 13, according to the suit.”

But Google is saying that New Mexico’s attorney general has it all wrong – Google Suite for Education gives schools the power to control kids’ account access, and requires schools to gain parental consent when necessary, a spokesperson for the company said. It’s all up to the schools how to properly use this tool. “We do not use personal information from users in primary and secondary schools to target ads.”

Even though Google claims this, it’s difficult to fully believe. CBS News points to a settlement Google was involved with in the fall of 2019, when it agreed to pay $170 million to settle federal and state allegations that “it had violated children’s privacy on YouTube by collecting personal information on kids without their parents’ consent.” This complaint, which was filed by the FTC and New York attorney general, claimed that the tech giant was using trackers to monitor kids, and use the collected data to advertise accordingly to kids.

The post What Decision Makers Need to Know About the Latest Lawsuit Against Google appeared first on My TechDecisions.