Space X Success Leads to New Heights

 

    Under the moonlight on the morning of April 23rd, Space X launched the companies third maned mission to the International Space Station.   The main goal of Space X was to create space travel that was almost routine, and Elon Musk and Space X have done that and succeeded greatly with it. 

    The April 23rd launch marked the first time that Space X has launched non-American astronauts. Along with two Americans, the crew consisted of one Japanese and one French astronaut to the International Space Station.  The astronauts will spend hours sitting in the dock, working with mission control to make sure all the systems are in check. Then after lift off, will spend over 23 hours in flight to the International Space Station. When the capsule reaches the International Space Station, the capsule will dock using an automated process already programmed into the capsule. Even after docking, the crews need to spend a few hours making sure that there is no air leaks in the dock. One air leak can create a vacuum in space and be deadly for all astronauts. 

    This launch did mark the second mission that was routine, using the same Crew Dragon spacecraft.  Musk now wants to get further revolutionize space travel by creating a reusable rocket, "The thing that's really important to revolutionize space is a rapidly reusable rocket...that is the gateway to the heavens."

    With the great success that Elon Musk and the entirety of the Space X company is experiencing, NASA has taken notice. NASA has their own sights set back onto the moon, especially after awarding Space X a new 2.9 billion dollar contract to build the new lander that NASA will use to bring humans back to the moon.  Elon Musk was honored that Space X was chosen saying, "It's a great honor to be chosen by NASA to return to the moon." The last time a human has set foot on the moon was the Apollo 17 mission in 1972. 

    Although, this time Musk has his sights set on something even more than just getting to the moon. "We don't want to be one of those single-planet species, we want to be a multi-planet species. " Musk has his next task of building a permanent base on the moon, and then even a city on Mars even further into the future. This new contract that NASA has awarded Space X to develop the lander, has the date set for 2024 when feet with touch the moon dust again. Although, Musk is not optimistic about the 2024 date set. Space X has had a history of not completing the projects on time, on average almost doubling the time projected. But there is no rush in space travel, especially when human lives are going to be involved. "We're going to build a lot of rockets, and then we're going to probably smash a bunch of them."  

Musk, and Space X had great success and will look for much more in the future. 

Source https://www.nytimes.com/live/2021/04/23/science/spacex-nasa-launch 

Are Hospitals and Other Healthcare Companies Keeping Your Data Safe?

        According to this article, the incidence of data breaches in medical and healthcare systems have increased greatly from prior years, as “over 40 million patient records were breached in 2020” alone, as the healthcare analytics and compliance company Protenus stated a few weeks ago on March 15, 2021.  This is mostly due to increased attempts and attacks using ransomware by hackers as well as insiders at a company or hospital wrongfully gathering sensitive information about patients such as “date of birth, inpatient/outpatient status, contact information, and other sensitive patient information”.  Overall, attempts made to hack healthcare data increased 42% since the pandemic began, which both surprises and does not surprise me given the opportunity that the pandemic gives scammers and the lack of security that healthcare companies seem to have regarding such sensitive information.

Overall, the opportunity that scammers and hackers have due to the pandemic allows for them to easily increase attempts at successfully gaining sensitive information into any company, especially healthcare companies or hospitals, since many companies, if not all, are moving to digitally store such information to allow for easier work from home for doctors, nurses, and other workers within these companies.  While easier access for employees may be useful under the current circumstances, it also has proven to be very dangerous for its data security for their patients.  In the case of employees misusing or stealing sensitive patient information, while employees will most certainly lose their jobs and possibly even face criminal charges for doing so, such companies should understand the risks posed by decreasing security for patients’ sensitive data and should actively work to prevent outside hackers and especially employees from easily gaining such information and harming the company as well as the patients whose information was stolen or sold to bad actors.  Especially in the healthcare field, I am very surprised at the lack of security for patients’ sensitive information even given the current circumstances.  

While I am surprised by the lack of security from companies that routinely handle such sensitive data for thousands of people, I am not surprised by the increase in attempts to gain such information both by disgruntled employees and outside hackers through ransomware.  Even though healthcare companies are an easy target during a pandemic given the nature of the crisis, theirs is one of very few industries where such sensitive information is vital to their operations, as insurance information is necessary to make claims, and social security numbers are often required for identification purposes.  Given this, it does not surprise me at all that hackers are increasing the rate of their attacks on healthcare as more and more people enter their systems and information flows more freely thanks to virtual work.  Likewise, healthcare companies often have to disclose such sensitive information to the government especially regarding the pandemic to track cases, deaths, and hospitalizations, creating another opportunity for data to be breached.  Overall, I am surprised by the nature of the attacks, but not the increase of them.

Source: https://www.prnewswire.com/news-releases/health-data-breaches-skyrocket-during-covid-19-pandemic-301247097.html

Marketing the Future: How Data Analytics is Changing

 Michael Steinrock

A third of Amazons sales come from their recommended “For You” page. Netflix’s “Shows and Movies you may Enjoy” feature has customers continually coming back for more viewing experience. Artificial intelligence and Data Analytics have been around for years, however recently it seems that companies have really been beginning to put a larger emphasis on them. Companies have began to invest billions upon billions in their data analytics and collection practices. This data is essentially priceless. Neil Hoyne says that “ The companies that are going to win are the ones who are using data, not guessing.” The article discusses how companies need to trust Artificial Intelligence to learn. Companies that invest money in AI need to let it do its work finding patterns in customers usage rates as well as purchasing habits. 

However, Artificial Intelligence does come with its risks. Jagadeesh describes that “AI can create social, reputational and regulatory risks, even for companies well-versed in technology. Amazon scrapped a recruiting software with a gender bias; Twitter shut down a Microsoft chatbot that “learned” how to post racists tweets; and Facebook was sued by the U.S. Department of Housing and Urban Development.” Artificial intelligence comes with great responsibility and at this moment not nearly as many rules and regulations as many other aspects of the business world. The way these companies use this data, monitoring it every minute of every day is in a sense “good business.” It makes sense to use every ounce of data at your disposal. However the question is do consumers know exactly what and how much data is being taken from them? Jagadeesh argues that the use of Artificial intelligence and data collection needs to be a priority for managers to keep an eye on. He recommends that companies should create interdisciplinary teams to continuously monitor and evaluate data for bias. However even though he warns of being cautions, he recognizes the immense benefits to Artificial Intelligence and Data Analytics in marketing and the business world. 

Jagadeesh describes that Data Analytics can really take the “guesswork” out of decision making. These programs and codes can make decisions so much easier for a company to make, since they are always growing and learning and obtaining new information. Take social media ads for example. Do you think that these ads that are popping up on your feed as you are scrolling are just random? Are they “guesses” by the social media company that this is something you may be interested in then? Absolutely not. These data analytic companies and social media sites use every single ounce of data that is at their disposal. Whether it is how long you view a certain post for, to what pictures you like, it is all eventually and meticulously sold right back at you. It will be very interesting in the next five year to see how AI grows, as well as what restriction come along with it. One thing is certain though, it’s not going away. 

Source: https://knowledge.wharton.upenn.edu/article/marketing-future-data-analytics-changing/

Data As An Inhibitor When Building AI Models

This article emphasizes the importance of having good quality data and strong practices around your data—like precision and timeliness—before starting to build efficient and accurate AI models. Although I don’t fully disagree with what the author is saying, I do believe a few key points need to be added.  First, not only can AI can help companies to improve customer experience automate business processes, but the outcomes from AI help to inform the business and guide the business stakeholders in their decision making and overall strategy.  Some examples of these decisions could be hiring, supplier sourcing, and more.  Next, it is not flawed data itself that creates the possibility for biased outcomes of AI models. It is the types of data being used to train the models, and the ways that those features impact the models, that lead to bias. Some issues that flawed data could create are extra cost, increased time and effort, and reduced efficiency for data scientists and engineers.  It takes time, resources, and money to access and clean up the data.

Additionally, there are more practices around making sure that you have good data to feed into your AI model than mentioned in the article. You must first be able to access it, which is a big part of the overall challenge, and you have to know how to interpret it.  There are several access methods that one could use, for example database APIs or some kind of data feed like ETL. For interpretation, you could use reverse engineering through discovery. You will of course need to find out the database API or the data feed type, or even make an assumption, to be able to use these methods to access and interpret it.  When it comes to data quality, Natural Language Processing (NLP) may be used as a way to structure the data so it is easy to consume.  

 

Other unmentioned inhibitors to performance when working with the data that goes into AI models include dependencies on other teams, varying institutional knowledge, the speed of change, and where the data sits.  For these, you need strong practices around governance, knowledge transfer, flexibility, and data harmony. It is very common for data to be spread across various data sources, or even across regions. This could create complexity and slow the user down when trying to access and harmonize it, not to mention the regulations they would need to comply with. 

 

For these reasons, is critical to be well equipped to manage the constant fast-paced changes, lack of harmony, and the level of quality of the data going into your AI model.  No human will be able to keep up without having the right tools and experts in place, and if you’re going to be successful, the right software investments must be made. It is not as simple as understanding how the data is gathered and cleaned as the author says—first and foremost you need visibility, the right tools could help get you there.

 

https://insidebigdata.com/2021/04/02/new-to-ai-adoption-dont-let-data-be-your-achilles-heel/

How Data Analytics is helping to solve food insecurity

 https://www.businessinsider.com/sc/data-analytics-helps-solve-food-insecurity-2021-3?utm_source=onsite&utm_medium=npu&utm_campaign=ing 

Feeding the World with Precision

In this particular article it speaks about how agriculture is making their businesses more efficient by the new use of data analytics. The new use of data analytics helps to make agriculture business more cost effective and profitable for the industry. The article touches upon some technological advancements as well that has helped to make the agriculture business more effective. 

With the agricultural business struggling even before the COVID-19 pandemic farmers are using new data analytics to help them farm more efficiently. The practice of using key inputs such as soil or weather for example, to then gather this data to make more accurate predictions is amazing. With all of the data that is being collected it can help farmers to farm more effectively and gives them a better chance at having a profitable business. Not only does it make it more profitable for them it also helps with the supply chain overall. The use of data analytics in agriculture is like a river flowing downhill and it will go down the chain to benefit all. With all the data that can be collected in today’s technological age I think that the use of data analytics is a vital source to keep agriculture efficient especially now with the pandemic. Not only does the use of data analytics help farming but it can help to prevent food wastage as well. The amount of food that is wasted away every year is mind blowing and the use of the data collected goes into making more sustainable storage of food. With the use of the data to help drive farmers towards better storage it can have a huge impact of food wastage across the globe. This to me is a big plus with the use of data analytics in agriculture as less food wasted through better food storage can help to lower the amount suffering from starvation. Another great technological advancement that the article touched upon was the use of feed additives. With the use of these feed additives it helped to reduce methane emissions as well as increase feed conversion. With the new feed additives it helps not only the farmers save money on feed but helping the environment as well. With less methane emissions put into the air it helps to stop more greenhouse gases from burning a hole in our atmosphere. I think that the use of feed additives should be used in every farm as it will help keep our planet cleaner as well as help farmers with costs. With new technology and data analytics the future is bright for agriculture and data analytics is the next step for the industry. Overall I think that the new use of data analytics will help to strengthen the agricultural business as well as the global supply chain.

18 Examples Of Big Data Analytics In Healthcare That Can Save People

    Big data is explained as a way to analyze data and extract information from data sources to then analyze and send it to a more complex data set. Big data is known for revealing patterns, trends, and associations relating to human behavior and interactions in particular. Obviously, big data has drastically changed the way we manage, analyze, and leverage data analytics within healthcare. 

    Healthcare analytics is the idea of understanding activities as a result of collecting data from the four areas of healthcare: claims and cost data, pharmaceutical and research development data, clinical data, and patient behavior and sentiment data. These four types of data play an important role in how data is collected in healthcare. Big data in healthcare is this ongoing idea of collecting large pieces of information through digital technologies that track patients records and the overall hospital management. One of the benefits of big data in healthcare is that there are lifesaving outcomes that come along with it. Because of the new forms of digital technology every year, mass forms of data is extracted which goes a long way and therefore has proven to cure cancers, cut down costs, prevent epidemics, which all leads to lives being saved. Within this article, the saying they tend to follow "prevention is better then cure" comes from the experience they have from collecting big data." With humans living longer nowadays, doctors have proven it to be successful getting to know their patients at an earlier stage rather then waiting until something goes wrong. Luckily, by using the digital technologies to gain insight and other information about the individual, they were able to "prevent" instead of "cure". I think this shows how important big data is in the real world. After reading this brief story in a hospital setting, it is evident how much collecting big data can help in eventually saving lives of humans. 

    Healthcare has eight-teen different examples of big data; however, two of these concepts jumped out to me. Firstly, using health data for informed strategic planning. This form of data explains how workers can analyze data from any demographic area to pull up information based on a patient to see why he or she is not taking their treatments. This is important because it caused works to give motivation to patients based off of the information they received. Secondly, big data might just cure cancer. This piece of data related back to the topic of data being able to cure cancer. Medical researchers can find trends and patterns in data that can help find ways to prevent cancers. By using this data, researchers are able to compare different data sets that have certain mutations and cancers to then come up with new solutions to eliminate the cancer completely.

    Clearly, big data in healthcare has many different roles and the end goal is to find new and easy solutions of eliminating cancer. They have found the use of digital technologies to collect big data extremely successful. 

https://www.datapine.com/blog/big-data-examples-in-healthcare/

Facebook Had a 500-Million User Data Leak: Now What?

Back in 2019, the Facebook data of around 500 million users was breached. That may sound like a lot, and is certainly nothing to scuffle at, but it actually isn't even in the top 15 largest breaches of all time. Nonetheless, just recently, that data was leaked to the public and is currently circling around the internet. To give you an idea, the types of data breached and leaked include things such as: profile names, Facebook ID numbers, email addresses, and phone numbers. That is, according to WIRED's article by Lily Hay Newman on the matter. Of course, as a side note, you can check to see if your data was leaked on HaveIBeenPwned. That will allow you to see if your phone number or email was exposed throughout the hack (and others). 

So what does this Facebook data leak mean in the macro sense? Well, unfortunately, unless you are someone who never uses the internet, it is quite likely you have had to put some of your sensitive information out there and that information will always remain, at least broadly, vulnerable to a data breach. In this case, and according the article, the data was vulnerable to attack due to a bug in Instagram's ability to import contacts. Some might think that this is Facebook's fault outright and was possibly a result of poor coding choices, and or data management, but it is far too complicated to tell. One shouldn't place blame completely on Facebook as things like this will happen from time to time, as unfortunate as they may be. After all, computers are only as good as the humans who use them, so human error is inevitable. In fact, it Facebook did make it clear that it did not expose this data intentionally, but it was scraped from their backend. 

Although, where Facebook could have done better was in acknowledgment of the breach, back when it happened, and or when the data was leaked recently. For example, the article mentions that The Irish Data Protection Commission said in a statement on Tuesday that it “received no proactive communication from Facebook" regarding the breach. This isn't best practice in my opinion, but perhaps there was good reason for not being so clear on the matter. 

So, back to the central question of this post: now what? What should you, as perhaps a Facebook user do now? The first thing you can do is check the website mentioned above to see if your data was leaked. After that, there is not much to do other than to be keep an eye out for spam emails, phone calls, and other malicious activity. 

It is a terrible day when data is breached, but this isn't going anywhere, and cybersecurity experts are in a constant battle. I think that if companies like Facebook keep coming up with new and innovative ways to encrypt data, it is possible to stop these types of attacks, but they will probably never go away all together. 

Source: https://www.wired.com/story/facebook-data-leak-500-million-users-phone-numbers/

The Human Element of Data Security

Conversations that were once face to face are now happening digitally worldwide. People are sending more emails than ever, and the pandemic has caused a massive influx of digital communication. This increase in digital communication poses new data threats and has caused new policies to be put into place in terms of data security. There is now an increased risk for people sending emails to the wrong recipients or attaching the wrong files to the wrong emails. Employees have also reported that they are more stressed and tired, and these factors could increase negligence. Companies must mitigate these risks and many companies have done so by implementing new data loss prevention tools.

I think companies need to implement these data loss prevention tools in a way that is productive and efficient. One confidential email to the wrong person or place could substantially harm a company and their reputation. Companies must find a healthy balance of data security while ensuring that they aren’t harming productivity within the company. If the tools are overly protective, they could slow employee production and subsequently harm the company. These tools can also cause employee frustration if they don’t align with real user behaviors and slow the employees down.

Fortunately, companies can now implement advanced data loss prevention tools that enhance security and productivity. These tools are now able to observe a user and understand the ways that they use email to share information and data. I think these advanced tools are effective because they only prompt users when they recognize abnormal behavior or heightened risks. I think that fewer notifications about security will make users more receptive to these messages because it will lessen click fatigue. If an employee is constantly clicking through security notifications, I think they will be less likely to take them seriously.

This type of advanced data loss prevention tool is essential in all types of business. Some employees share sensitive and private information through emails hourly and it is important that these emails are protected. Hacking and security breaches are always a risk, but companies can mitigate the risks of leaks by implementing data loss prevention tools.

Certain companies run a severe risk of leaking insider information to the public and one email could destroy an entire corporation. I think that this type of data security is especially essential in the accounting and finance industry. The “big four” accounting firms audit large corporations and have an abundance of financial information on clients. A lot of this information shared within these accounting firms is private and would be considered “insider information.” If this information was leaked, it would be devastating for the firms. Insider information would allow investors to have an unfair advantage in terms of whether or not to invest in a company.

Regardless of the industry, any security breach can be catastrophic. I think it is crucial for companies to recognize this and implement the necessary measures to protect themselves.

Source: https://builtin.com/cybersecurity/advanced-data-protection-tools 

New Facebook Data Breach

Over the weekend it was reported that data from over 500 million Facebook users was found online for purchase. However this is no surprise, as it is just one case of many instances where user data was been stolen or leaked after it was taken by Facebook. Back in 2018 and 2019 there were two big cases where a combined 354 million user's data was leaked online that including information such as full names and phone numbers. The site claims that this data was several years old however, and that it was part of the 2019 breach that was subsequently dealt with. With this leak, user's phone numbers, locations, birthdates, full names and emails were available for purchase to hackers online, just to be dismissed by the company. This news holds a very important message about data security and social media that is often ignored by users, and that's the risk you take when you give these sites your personal information.

It's not just Facebook that takes your data for economic gain. Companies like Twitter, Instagram, Tinder, Uber, Spotify, etc all take your information for various reasons, but most do with the intention to sell to advertising companies. These companies require data to present relevant ads to you, to help companies trying to sell you things make money. Its a process that entirely forgets about the users, and ignores their rights for the pursuit of capital gain, subsequently endangering users in the process. With identity theft as the biggest threat coming from these leaks, it exposes another problem with companies that lack motivation to effectively protect your private data. If you remember the Equifax leak from back in 2017, 148 million user's Social Security numbers, birth dates, home addresses, tax ID numbers, driver's license info and more were stolen by hackers. It put into perspective how prone companies are to being hacked, something that could have way larger implications than just identity theft (which is already a big deal).

According to a study by Deloitte and the ISACA, companies spend on average 10% of their revenue on cybersecurity each year. However, 60% of survey respondents said that their companies cybersecurity is underfunded. With companies susceptible to DDoS attacks, data breaches and employees succumbing to email fishing attempts that could potentially lead to devastating releases of user data, I think that companies should increase their cybersecurity spending with the users in mind. Focusing on other aspects of your company make sense from the capitalist mindset that a CEO possesses, but users have a right to their data being secure online. 

I've linked a short but very useful video on how the Equifax leak happened.

https://apnews.com/article/business-media-social-media-fce118b1adfef8f6c51518f71465dd4b

https://www.ramseysolutions.com/insurance/data-breach-impacts

https://cybersecurity.att.com/blogs/security-essentials/how-to-justify-your-cybersecurity-budget

How Predictive Analytics Can Help At-Risk College Students

For universities, retention rates are a key indicator of the school’s ability to meet the needs and expectations of its students. Having a low retention reflects poorly on the school and makes it less likely for incoming students to apply. In 2014, Crown College in Minnesota updated their retention strategy using a new approach they called Persistence and Completion combined with data analytics techniques from Jenzabar Technology. According to the article, they compiled and mined data from “first-time, full-time degree-seeking students who entered the college in fall semesters of 2009 – 2014” from which they created a regression model to predict the likelihood of retention for at-risk students. It first ran this model in fall 2015 against incoming full-time freshmen in its School of Arts and Sciences and continued to use the model for the next six semesters. After implementing the program, freshman retention rose from 84 percent in 2015 to 89 percent of freshmen in 2019, and retention of all eligible students rose from 90 to 94 percent for the same years.

 

At face value, I like this initiative for a number of reasons. Though many schools try not to appear like a business, most operate like one. From a business perspective, an initiative like this can help universities stay competitive or even exceed their competition in retention rates. I also thought that being able to accurately forecast the chance of at-risk students unenrolling enables schools to give those students targeted support rather than either detecting the risk too late or simply waiting for the student to ask for help.  

 

Despite my satisfaction with Crown College’s success story, the article left out many key details about their analytical process. First, they mentioned the school identified nine factors that could predict a student’s risk of unenrolling, but they didn’t say what any of these factors were. I would like to know these factors to gain some insights into what the school was evaluating and how it could yield such accurate predictions. Similarly, the article mentioned that the most successful implementations of this retention plan at other universities has been evaluating students at the beginning of the term. Thus, I wondered how accurate the model is across different grade levels since a freshman would presumably have much less data to factor than a rising senior. Furthermore, since retention is usually a higher concern for underclassmen, this makes we want to know even more what metrics are being used to evaluate risk during the earliest months of a student’s college career. I would venture that it is more difficult to support freshman as their retention rates were lower than that of all eligible students both before and after the Persistence and Completion program. 

 

Overall, I enjoyed this article and was impressed by the use of data to support students in need. Additionally, with some additional research I found that Crown College was able to put its retention rates on par with more selective colleges who average at or below 25% acceptance. 

 

“The Condition of Education - Undergraduate Retention and Graduation Rates - Indicator April (2020).” The Condition of Education, National Center for Education Statistics, Apr. 2020, nces.ed.gov/programs/coe/indicator_ctr.asp. 

Zaino, Jennifer. “Case Study: Crown College Uses Predictive Analytics to Retain At-Risk Students.” Dataversity, Dataversity, 4 Feb. 2021, www.dataversity.net/case-study-crown-college-uses-predictive-analytics-to-retain-at-risk-students/. 

Facebook Breached Again

In a recent scandal concerning personal data, Facebook has suffered yet another data breach. Facebook is beginning to follow a disturbing pattern of data hacks leading to millions of users having their personal information extracted by hackers and leaked into the public. In the most recent attack, in 106 countries 533 million Facebook user's personal information was hacked. This included cell phone numbers, birthdates, and locations that have been leaked to the public. The breach is supposedly linked to a vulnerability that was said to have been “patched” in 2019. The chief technology officer of the cybercrime intelligence firm Hudson Rock, Alon Gal, mentioned that while the data has already been leaked, Facebook cannot do much to help. They can only further remind users to watch out for phishing and scams.  

In review of this event, I find many issues. 

The prominent issue of personal information, including details of location and birthdate, being easily hacked is the main problem. While personal information being hacked is not a new concept, the scope of this data breach is far reaching. The private security laws that have been broken among the 106 countries affected must be extensive, especially considering the highly restrictive laws in the European Union. 

 

Laws and restrictions progress into the second issue of Facebook recognizing the vulnerability a couple years ago due to scraping capabilities that were in violation of its terms and services. This knowledge leads me to the question, if the problem happened before and appropriate measures were said to have been put into place, why did it happen again? Obviously, measures were not taken far enough for one of the company's largest breaches to have happened after supposedly sufficient measures were put into place to fix the issue. The track record of data breaches on Facebook makes me question the integrity of the company and ability to keep their customers information safe. I would personally begin to question my value and relationship with the company after so many failures. 

Lastly, I find it interesting that Gal would suggest that the company merely remind the users to be cognizant of phishing schemes rather than encourage the company to reassess their insufficient security measures. While it is important for users to be aware of what corrupt links and posts may look like, I believe the main problem lies within the values and technology of the company itself. I do not find the responsibility to lie on the customers who entrust their personal information to a company. The company, Facebook, should take the time to protect and defend against attacks on their users. 

I find that throughout the years Facebook has proven itself to not take the responsibility of its users' private information seriously. For continuous hacks to keep affecting millions around the world, the appropriate measures are clearly not being taken. Perhaps the company should start hiring hackers to try to purposefully break into the company and work together to find an effective solution. 

Source: https://www.businessinsider.com/stolen-data-of-533-million-facebook-users-leaked-online-2021-4