Tag Archives: Happy
Happy? New Year
I know it has been a few days since I last posted something. But lately there has been a lack of new news. The Republicans continue to kowtow to Trump, and Americans continue to die from Covid-19 in record numbers. The only new news happening in the near future is the two Senate elections in Georgia that are happening next week, which will determine the fate of the Senate.
I’m actually posting to thank everyone who reads this blog, and especially those who leave comments. You’ve helped to keep me sane during 2020. I hope everyone survived ok, and wish that 2021 is much brighter for everyone. I’ll keep posting, as long as you keep reading and commenting.

this is far better happy talk: “What we need is more ‘economic intercourse'”
Giggling RWNJs seized on a Biden comment that only reveals how much context will be needed with an IMPOTUS who’s a pathological liar.
For example, Trump lied again today:
Better, not more
President Trump’s first tweet Sunday came unusually late, popping up a few minutes after noon — hours behind schedule for a president who is often awake and tweeting as the sun rises.
“Happy Birthday to Melania, our great First Lady!” Trump tweeted at 12:06 p.m.
The celebratory tweet kicked off a long day of tweeting and retweeting that really ramped up at around 2 p.m. when Trump observed, in response to a recent New York Times article, that those who know him regard him as “the hardest working President in history.”
Over the next seven hours or so, Trump took aim at everything and anyone he could, unleashing a barrage of more than two dozen tweets and retweets that targeted media outlets, high-profile commentators and hosts, and Democrats.
He also returned once more to the Russia probe and impeachment, promoting a tweet that accused his political adversaries of “three failed coup attempts.” The tweet went on to suggest with no evidence that the president’s opponents could “attempt to steal the election” by making the novel coronavirus’s impact on human lives seem worse than it really is.
Happy New Year from Power BI Desktop!

Happy New Year!
In honor of the new year, our team put together this fun video where we reveal what makes Power BI what it is today! Enjoy!
This month we will have a Power BI Report Server update only, but starting February, Power BI Desktop will continue our monthly ship cadence.
Looking forward to another great year!
Happy New Year from Power BI Desktop!

Happy New Year !
With over 150 features released, 2018 has been a prolific year for Power BI Desktop!
To cap off this successful year, our team put together a fun video, showcasing our pick for the 5 favorite releases of 2018:
- Report page tooltips [March]
- Web by example [May]
- Composite models [July] + aggregations [September]
- Expand + collapse [November]
- New filter experience [November]
We’ve also added an Honorable Mention for the Accessibility features released this year, which include the improved formula bar, adding filters from the context menu, and more!
We hope you enjoy the video and would love to hear about your favorite five!
This month we will have a Power BI Report Server update only, but starting February, Power BI Desktop will continue our monthly ship cadence. Looking forward to an even more impactful 2019!
Happy Holidays from Act-On! Our Gift to You? 3 Tips for Engaging Customers in the New Year

As we reflect on the past year, we are most grateful for our customers, our co-workers, and our passion for empowering marketers like you, with top-notch marketing automation
We realize that doing great work does not only require the right tools, but also the right skills and mindset. And having a strong customer focus, meaning that you really understand and engage your customers, is an important part of a successful marketing strategy.
That is why, to celebrate the holidays, we want to share a few of our tips on how to best engage customers. So, if you are as enthusiastic about customer marketing as we are, here are a few ways you can enhance your efforts in 2019.
1. Drive traffic with fresh content
We’ve written several blog posts about the importance of content in the past year, such as this one and this one, and the reason why is that it is still an excellent way to attract more inbound traffic, offer useful information to leads and, of course, engage current customers.
While whitepapers and eBooks are a great tactic when it comes to moving leads through the sales funnel, you should also aim to create fun and refreshing content for your current customers. Make sure to diversify your efforts and create compelling content in various formats like video, podcasts, webinars, and storytelling infographics. Variety keeps things interesting for your current customers and drives engagement.
For example, the video above was just one component of our customer newsletter, which features tips and advice, shines the spotlight on customers who are doing brilliant things, and informs our customers of upcoming events. These types of efforts not only ensure that your customers feel like they are always top of mind, but also offer them something beneficial that enables them to continue to see the value of your service or product.
But, focusing on content that is just fun is also very important. The video, in particular, is intended to remind our customers that we care about them and show them a different side to our company, rather than push our product.
2. Connect with your customers and collect feedback
Whether it’s a quick email, a check-in phone call or invite to an event, nothing makes customers feel more special than seeing you make an effort to personally reach out to see how they are doing and gather their feedback. This gesture demonstrates good marketing and customer service, and inspires loyalty among your consumers. Being able to connect with a person, not just a brand, is a great way to remind them that you have their best interest in mind and are committed to enhancing their life in some way.
More importantly, taking the time to touch base with customers is beneficial to you as a marketer because it’s a great opportunity to collect insights that can inform and strengthen your future marketing efforts. For example, a conversation with a customer can lead to your next great content idea. Or, you’ll learn from them what is a hit or miss when it comes to engaging customers, which will help you improve the personalization of your future marketing efforts.
3. Make it personal
Speaking of personalizing your marketing efforts, it is truly important to connect with your audience in personal, high-touch ways that show them they are important and top-of-mind. This goes beyond including their name in an email, and requires you to know a thing or two about the customer you’re speaking to, such as their industry, interests, and primary pain points.
But, personalizing your marketing is much simpler and efficient than you think. The right marketing automation tool, like Act-On, provides you with tools to collect customer information, enables you to segment customers into specific lists so you’re always sending them relevant and tailored information, and includes a variety of templates allowing you to easily send emails and build landing pages that appeal to each of your customer segments. We are marketers like you. We know your pain and your challenges and are here to support you on your quest to become a marketing superstar.
To end, we wish you a very happy holiday season and a new year filled with marketing magic. We hope that these tips serve you well in the new year, and we’re excited to hear which of these you’ll be implementing into your marketing strategy in the upcoming months. And of course, in the spirit of this post, we know that we can also learn from our customers, so we’d love to hear your tips for better customer engagement as well.
Happy Thanksgiving 2018
Behold! Somewhere in the midst of whip cream heaven, lies a piece of pumpkin pie.
“The only way to eat Pumpkin Pie!”
Image courtesy of https://imgur.com/gallery/K0Tmcz0.
Happy Halloween!
The scariest things this Halloween are Fox News and Donald Trump. Even though they are trying to scare everyone by claiming that the US is being invaded by immigrants. You know, immigrants, like the ancestors of almost everyone in the US. Indeed, the immigrants already invaded, long ago.
Also published on Medium.
Happy New Year from Power BI Desktop
Happy New Year!
We’ve had a fantastic six months on the Power BI Desktop team and wanted to do a little round-up of some of the highlights. We made a little video for you all to say thanks for your support and feedback, and to give our team a chance to show some of their favorite moments. There’s a tradition in the Microsoft BI world of having the product team sign the boxes of shipping products, but since moving to services we can’t do that any more! So we made a poster with all our big features from the last 6 months and got the team to sign that instead:
Thanks again and here’s to a fantastic 2018!
Happy New Year 2018
The Peanuts gang
“Happy New Year my fellow imgurians!.”
Image courtesy of https://imgur.com/gallery/0ClTNeQ.
Mining Big Data To Create Smart Products And Happy Customers
Last August, a woman arrived at a Reno, Nevada, hospital and told the attending doctors that she had recently returned from an extended trip to India, where she had broken her right thighbone two years ago. The woman, who was in her 70s, had subsequently developed an infection in her thigh and hip for which she was hospitalized in India several times. The Reno doctors recognized that the infection was serious—and the visit to India, where antibiotic-resistant bacteria runs rampant, raised red flags.
When none of the 14 antibiotics the physicians used to treat the woman worked, they sent a sample of the bacterium to the U.S. Centers for Disease Control (CDC) for testing. The CDC confirmed the doctors’ worst fears: the woman had a class of microbe called carbapenem-resistant Enterobacteriaceae (CRE). Carbapenems are a powerful class of antibiotics used as last-resort treatment for multidrug-resistant infections. The CDC further found that, in this patient’s case, the pathogen was impervious to all 26 antibiotics approved by the U.S. Food and Drug Administration (FDA).
In other words, there was no cure.
This is just the latest alarming development signaling the end of the road for antibiotics as we know them. In September, the woman died from septic shock, in which an infection takes over and shuts down the body’s systems, according to the CDC’s Morbidity and Mortality Weekly Report.
Other antibiotic options, had they been available, might have saved the Nevada woman. But the solution to the larger problem won’t be a new drug. It will have to be an entirely new approach to the diagnosis of infectious disease, to the use of antibiotics, and to the monitoring of antimicrobial resistance (AMR)—all enabled by new technology.

Abuse and overuse of antibiotics in healthcare and livestock production have enabled bacteria to both mutate and acquire resistant genes from other organisms, resulting in truly pan-drug resistant organisms. As ever-more powerful superbugs continue to proliferate, we are potentially facing the deadliest and most costly human-made catastrophe in modern times.
“Without urgent, coordinated action by many stakeholders, the world is headed for a post-antibiotic era, in which common infections and minor injuries which have been treatable for decades can once again kill,” said Dr. Keiji Fukuda, assistant director-general for health security for the World Health Organization (WHO).
Even if new antibiotics could solve the problem, there are obstacles to their development. For one thing, antibiotics have complex molecular structures, which slows the discovery process. Further, they aren’t terribly lucrative for pharmaceutical manufacturers: public health concerns call for new antimicrobials to be financially accessible to patients and used conservatively precisely because of the AMR issue, which reduces the financial incentives to create new compounds. The last entirely new class of antibiotic was introduced 30 year ago. Finally, bacteria will develop resistance to new antibiotics as well if we don’t adopt new approaches to using them.
Technology can play the lead role in heading off this disaster. Vast amounts of data from multiple sources are required for better decision making at all points in the process, from tracking or predicting antibiotic-resistant disease outbreaks to speeding the potential discovery of new antibiotic compounds. However, microbes will quickly adapt and resist new medications, too, if we don’t also employ systems that help doctors diagnose and treat infection in a more targeted and judicious way.
Indeed, digital tools can help in all four actions that the CDC recommends for combating AMR: preventing infections and their spread, tracking resistance patterns, improving antibiotic use, and developing new diagnostics and treatment.
Meanwhile, individuals who understand both the complexities of AMR and the value of technologies like machine learning, human-computer interaction (HCI), and mobile applications are working to develop and advocate for solutions that could save millions of lives.
Keeping an Eye Out for Outbreaks
Like others who are leading the fight against AMR, Dr. Steven Solomon has no illusions about the difficulty of the challenge. “It is the single most complex problem in all of medicine and public health—far outpacing the complexity and the difficulty of any other problem that we face,” says Solomon, who is a global health consultant and former director of the CDC’s Office of Antimicrobial Resistance.
Solomon wants to take the battle against AMR beyond the laboratory. In his view, surveillance—tracking and analyzing various data on AMR—is critical, particularly given how quickly and widely it spreads. But surveillance efforts are currently fraught with shortcomings. The available data is fragmented and often not comparable. Hospitals fail to collect the representative samples necessary for surveillance analytics, collecting data only on those patients who experience resistance and not on those who get better. Laboratories use a wide variety of testing methods, and reporting is not always consistent or complete.
Surveillance can serve as an early warning system. But weaknesses in these systems have caused public health officials to consistently underestimate the impact of AMR in loss of lives and financial costs. That’s why improving surveillance must be a top priority, says Solomon, who previously served as chair of the U.S. Federal Interagency Task Force on AMR and has been tracking the advance of AMR since he joined the U.S. Public Health Service in 1981.
A Collaborative Diagnosis
Ineffective surveillance has also contributed to huge growth in the use of antibiotics when they aren’t warranted. Strong patient demand and financial incentives for prescribing physicians are blamed for antibiotics abuse in China. India has become the largest consumer of antibiotics on the planet, in part because they are prescribed or sold for diarrheal diseases and upper respiratory infections for which they have limited value. And many countries allow individuals to purchase antibiotics over the counter, exacerbating misuse and overuse.
In the United States, antibiotics are improperly prescribed 50% of the time, according to CDC estimates. One study of adult patients visiting U.S. doctors to treat respiratory problems found that more than two-thirds of antibiotics were prescribed for conditions that were not infections at all or for infections caused by viruses—for which an antibiotic would do nothing. That’s 27 million courses of antibiotics wasted a year—just for respiratory problems—in the United States alone.
And even in countries where there are national guidelines for prescribing antibiotics, those guidelines aren’t always followed. A study published in medical journal Family Practice showed that Swedish doctors, both those trained in Sweden and those trained abroad, inconsistently followed rules for prescribing antibiotics.
Solomon strongly believes that, worldwide, doctors need to expand their use of technology in their offices or at the bedside to guide them through a more rational approach to antibiotic use. Doctors have traditionally been reluctant to adopt digital technologies, but Solomon thinks that the AMR crisis could change that. New digital tools could help doctors and hospitals integrate guidelines for optimal antibiotic prescribing into their everyday treatment routines.
“Human-computer interactions are critical, as the amount of information available on antibiotic resistance far exceeds the ability of humans to process it,” says Solomon. “It offers the possibility of greatly enhancing the utility of computer-assisted physician order entry (CPOE), combined with clinical decision support.” Healthcare facilities could embed relevant information and protocols at the point of care, guiding the physician through diagnosis and prescription and, as a byproduct, facilitating the collection and reporting of antibiotic use.

Cincinnati Children’s Hospital’s antibiotic stewardship division has deployed a software program that gathers information from electronic medical records, order entries, computerized laboratory and pathology reports, and more. The system measures baseline antimicrobial use, dosing, duration, costs, and use patterns. It also analyzes bacteria and trends in their susceptibilities and helps with clinical decision making and prescription choices. The goal, says Dr. David Haslam, who heads the program, is to decrease the use of “big gun” super antibiotics in favor of more targeted treatment.
While this approach is not yet widespread, there is consensus that incorporating such clinical-decision support into electronic health records will help improve quality of care, contain costs, and reduce overtreatment in healthcare overall—not just in AMR. A 2013 randomized clinical trial finds that doctors who used decision-support tools were significantly less likely to order antibiotics than those in the control group and prescribed 50% fewer broad-spectrum antibiotics.
Putting mobile devices into doctors’ hands could also help them accept decision support, believes Solomon. Last summer, Scotland’s National Health Service developed an antimicrobial companion app to give practitioners nationwide mobile access to clinical guidance, as well as an audit tool to support boards in gathering data for local and national use.
“The immediacy and the consistency of the input to physicians at the time of ordering antibiotics may significantly help address the problem of overprescribing in ways that less-immediate interventions have failed to do,” Solomon says. In addition, handheld devices with so-called lab-on-a-chip technology could be used to test clinical specimens at the bedside and transmit the data across cellular or satellite networks in areas where infrastructure is more limited.
Artificial intelligence (AI) and machine learning can also become invaluable technology collaborators to help doctors more precisely diagnose and treat infection. In such a system, “the physician and the AI program are really ‘co-prescribing,’” says Solomon. “The AI can handle so much more information than the physician and make recommendations that can incorporate more input on the type of infection, the patient’s physiologic status and history, and resistance patterns of recent isolates in that ward, in that hospital, and in the community.”
Speed Is Everything
Growing bacteria in a dish has never appealed to Dr. James Davis, a computational biologist with joint appointments at Argonne National Laboratory and the University of Chicago Computation Institute. The first of a growing breed of computational biologists, Davis chose a PhD advisor in 2004 who was steeped in bioinformatics technology “because you could see that things were starting to change,” he says. He was one of the first in his microbiology department to submit a completely “dry” dissertation—that is, one that was all digital with nothing grown in a lab.
Upon graduation, Davis wanted to see if it was possible to predict whether an organism would be susceptible or resistant to a given antibiotic, leading him to explore the potential of machine learning to predict AMR.

As the availability of cheap computing power has gone up and the cost of genome sequencing has gone down, it has become possible to sequence a pathogen sample in order to detect its AMR resistance mechanisms. This could allow doctors to identify the nature of an infection in minutes instead of hours or days, says Davis.
Davis is part of a team creating a giant database of bacterial genomes with AMR metadata for the Pathosystems Resource Integration Center (PATRIC), funded by the U.S. National Institute of Allergy and Infectious Diseases to collect data on priority pathogens, such as tuberculosis and gonorrhea.
Because the current inability to identify microbes quickly is one of the biggest roadblocks to making an accurate diagnosis, the team’s work is critically important. The standard method for identifying drug resistance is to take a sample from a wound, blood, or urine and expose the resident bacteria to various antibiotics. If the bacterial colony continues to divide and thrive despite the presence of a normally effective drug, it indicates resistance. The process typically takes between 16 and 20 hours, itself an inordinate amount of time in matters of life and death. For certain strains of antibiotic-resistant tuberculosis, though, such testing can take a week. While physicians are waiting for test results, they often prescribe broad-spectrum antibiotics or make a best guess about what drug will work based on their knowledge of what’s happening in their hospital, “and in the meantime, you either get better,” says Davis, “or you don’t.”
At PATRIC, researchers are using machine-learning classifiers to identify regions of the genome involved in antibiotic resistance that could form the foundation for a “laboratory free” process for predicting resistance. Being able to identify the genetic mechanisms of AMR and predict the behavior of bacterial pathogens without petri dishes could inform clinical decision making and improve reaction time. Thus far, the researchers have developed machine-learning classifiers for identifying antibiotic resistance in Acinetobacter baumannii (a big player in hospital-acquired infection), methicillin-resistant Staphylococcus aureus (a.k.a. MRSA, a worldwide problem), and Streptococcus pneumoniae (a leading cause of bacterial meningitis), with accuracies ranging from 88% to 99%.
Houston Methodist Hospital, which uses the PATRIC database, is researching multidrug-resistant bacteria, specifically MRSA. Not only does resistance increase the cost of care, but people with MRSA are 64% more likely to die than people with a nonresistant form of the infection, according to WHO. Houston Methodist is investigating the molecular genetic causes of drug resistance in MRSA in order to identify new treatment approaches and help develop novel antimicrobial agents.

The Hunt for a New Class of Antibiotics
There are antibiotic-resistant bacteria, and then there’s Clostridium difficile—a.k.a. C. difficile—a bacterium that attacks the intestines even in young and healthy patients in hospitals after the use of antibiotics.
It is because of C. difficile that Dr. L. Clifford McDonald jumped into the AMR fight. The epidemiologist was finishing his work analyzing the spread of SARS in Toronto hospitals in 2004 when he turned his attention to C. difficile, convinced that the bacteria would become more common and more deadly. He was right, and today he’s at the forefront of treating the infection and preventing the spread of AMR as senior advisor for science and integrity in the CDC’s Division of Healthcare Quality Promotion. “[AMR] is an area that we’re funding heavily…insofar as the CDC budget can fund anything heavily,” says McDonald, whose group has awarded $ 14 million in contracts for innovative anti-AMR approaches.
Developing new antibiotics is a major part of the AMR battle. The majority of new antibiotics developed in recent years have been variations of existing drug classes. It’s been three decades since the last new class of antibiotics was introduced. Less than 5% of venture capital in pharmaceutical R&D is focused on antimicrobial development. A 2008 study found that less than 10% of the 167 antibiotics in development at the time had a new “mechanism of action” to deal with multidrug resistance. “The low-hanging fruit [of antibiotic development] has been picked,” noted a WHO report.
Researchers will have to dig much deeper to develop novel medicines. Machine learning could help drug developers sort through much larger data sets and go about the capital-intensive drug development process in a more prescriptive fashion, synthesizing those molecules most likely to have an impact.
McDonald believes that it will become easier to find new antibiotics if we gain a better understanding of the communities of bacteria living in each of us—as many as 1,000 different types of microbes live in our intestines, for example. Disruption to those microbial communities—our “microbiome”—can herald AMR. McDonald says that Big Data and machine learning will be needed to unlock our microbiomes, and that’s where much of the medical community’s investment is going.
He predicts that within five years, hospitals will take fecal samples or skin swabs and sequence the microorganisms in them as a kind of pulse check on antibiotic resistance. “Just doing the bioinformatics to sort out what’s there and the types of antibiotic resistance that might be in that microbiome is a Big Data challenge,” McDonald says. “The only way to make sense of it, going forward, will be advanced analytic techniques, which will no doubt include machine learning.”
Reducing Resistance on the Farm
Bringing information closer to where it’s needed could also help reduce agriculture’s contribution to the antibiotic resistance problem. Antibiotics are widely given to livestock to promote growth or prevent disease. In the United States, more kilograms of antibiotics are administered to animals than to people, according to data from the FDA.
One company has developed a rapid, on-farm diagnostics tool to provide livestock producers with more accurate disease detection to make more informed management and treatment decisions, which it says has demonstrated a 47% to 59% reduction in antibiotic usage. Such systems, combined with pressure or regulations to reduce antibiotic use in meat production, could also help turn the AMR tide.

Breaking Down Data Silos Is the First Step
Adding to the complexity of the fight against AMR is the structure and culture of the global healthcare system itself. Historically, healthcare has been a siloed industry, notorious for its scattered approach focused on transactions rather than healthy outcomes or the true value of treatment. There’s no definitive data on the impact of AMR worldwide; the best we can do is infer estimates from the information that does exist.
The biggest issue is the availability of good data to share through mobile solutions, to drive HCI clinical-decision support tools, and to feed supercomputers and machine-learning platforms. “We have a fragmented healthcare delivery system and therefore we have fragmented information. Getting these sources of data all into one place and then enabling them all to talk to each other has been problematic,” McDonald says.
Collecting, integrating, and sharing AMR-related data on a national and ultimately global scale will be necessary to better understand the issue. HCI and mobile tools can help doctors, hospitals, and public health authorities collect more information while advanced analytics, machine learning, and in-memory computing can enable them to analyze that data in close to real time. As a result, we’ll better understand patterns of resistance from the bedside to the community and up to national and international levels, says Solomon. The good news is that new technology capabilities like AI and new potential streams of data are coming online as an era of data sharing in healthcare is beginning to dawn, adds McDonald.
The ideal goal is a digitally enabled virtuous cycle of information and treatment that could save millions of dollars, lives, and perhaps even civilization if we can get there. D!
Read more thought provoking articles in the latest issue of the Digitalist Magazine, Executive Quarterly.
About the Authors:
Dr. David Delaney is Chief Medical Officer for SAP.
Joseph Miles is Global Vice President, Life Sciences, for SAP.
Walt Ellenberger is Senior Director Business Development, Healthcare Transformation and Innovation, for SAP.
Saravana Chandran is Senior Director, Advanced Analytics, for SAP.
Stephanie Overby is an independent writer and editor focused on the intersection of business and technology.