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In The Data Science Playground, The First Lesson Is DataOps – Forbes

LONDON - DECEMBER 18: A concrete surfaced playground is shown December 18, 2002 in London. School ... [+] playing fields are being sold off at a rate of almost one a week despite government assurances that the Conservative policy of selling sports grounds would be reversed. (Photo by John Li/Getty Images)

The very fabric of cloud is still forming. As fast as we solidify elements of cloud computing structures, networks and services in order to agree how they should best be architected, deployed and managed... there is an equal and opposite stream of new development that sees sometimes quite esoteric techniques, best-practices and methodologies come to the fore.

Already past its esoteric adolescence and into mainstream deployment and onward augmentation is the concept of Infrastructure-as-Code (IaC).

This approach to base layer cloud network services creation sees the steps required to provision infrastructure such as servers, data storage and networks being represented as software code (or some form of descriptive model). It has already become increasingly common as organizations look to streamline their IT processes and reduce the amount of time to create (and destroy i.e. retire and decommission) IT infrastructure.

Typically incorporated into an organizations DevOps strategy, IaC, which has historically been used to facilitate the creation of virtualized environments, is now seen as a key building block for automating the configuration and provisioning of the services provided by hyperscalers and other technologies that comprise todays polycloud environments.

All well and good so far then, yes. But as we now also look to extend our use of data science at a core operational level, the use of IaC needs to be revisited to give it not just DevOps goodness, but DataOps wellbeing at the same time. This is the opinion of Nelson Petracek in his role as global CTO with Tibco, a company known for its data-centric cloud platform technologies.

Petracek says that data science is driving the most progressive business models out there. This is the creation of data-driven decision intelligence, data-centric business modeling and the use of Artificial Intelligence (AI) and Machine Learning (ML) in all its forms.

But he argues, as we engineer data science into the operational fabric of business running on Infrastructure-as-Code (IaC) cloud implementations, automating traditional infrastructure provisioning is not enough and supporting DevOps capabilities is not sufficient

The need for automation in the world of data science is not just about the software, services and applications, but also the data itself, said Petracek.

Thus, IaC has a new role to play, one focused on the DataOps processes needed for todays modern data fabric, data mesh and data management architectures.

The difference between DevOps and DataOps is another discussion in and of itself, but - in general - DataOps includes not just DevOps principles for accelerating the creation of analytics products, but also other methodologies needed to optimize the use, delivery, and value of data within an organization, stated Petracek.

Amongst other capabilities, the Tibco CTO explains that DataOps involves the data workflows and processes needed to deliver high quality data and results to data consumers in a timely and contextual fashion. This is not the realm of DevOps, which instead focuses on the end-to-end delivery of software products and services.

As a result, IaC in the data science world must be extended beyond DevOps and IT infrastructure creation. Servers, storage and networks still need to be provisioned, but so do data warehouse table structures, data pipelines, data quality checks, model validations and various other supporting infrastructure elements, clarified Petracek.

So what we have here is not just cloud infrastructure and not just composable turn-off-and-onable Infrastructure-as-Code (IaC), we have DataOps-Aware Cloud IaC (or DOACIaC, an acronym that doesnt actually exist).

From Petraceks viewpoint, IaC techniques do indeed have the ability to capture these much more DataOps compliant elements of Infrastructure-as-Code and subsequently provide a number of benefits.

There benefits would include improved repeatability, simplified maintenance and reduced configuration errors. A reduction in the amount of time and effort required to create or tear down an environment, along with any software application or data service dependencies. Versions of each dependency can be fixed, eliminating incompatibilities and unexpected execution results.

We also get the chance to move forward towards improved audit processes, as the IaC artifacts may be stored and versioned in a shared repository. It is possible to access this history to prove the environment and data-related configurations associated with a particular analysis or data process at any point in time, said Petracek, who also points to new opportunities for more rapid experimentation, streamlined data science playground creation and cross-team collaboration.

Tibcos Petracek concludes by saying that this DataOps-enriched approach to cloud infrastructure enables greater re-use, simplified migrations to different environments and reduced support requirements.

The definition of Infrastructure as Code (IaC) is expanding as organizations attempt to improve the speed, accuracy and value of their data pipelines. Successful enterprises understand that DataOps should be their focus, with DevOps a subset of that strategy. Perhaps the time has come for IaC to take on an expanded role as well, he concluded.

Software application development, data science and related aspects of cloud engineering are fond of using schoolyard metaphors already; we know that sandboxing techniques describe the ability for kids (in this case: software professionals, data scientists and citizen software/data non-techies too) to mess around with ideas that dont create a mess for everyone else. Extending sandboxes to a wider notion of the data science playground is arguably a logical move.

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In The Data Science Playground, The First Lesson Is DataOps - Forbes

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BLM, Reuters, and the Price of Dissent – City Journal

Zac Kriegman had the ideal rsum for the professional-managerial class: a bachelors in economics from Michigan and a J.D. from Harvard and years of experience with high-tech startups, a white-shoe law firm, and an econometrics research consultancy. He then spent six years at Thomson Reuters Corporation, the international media conglomerate, spearheading the companys efforts on artificial intelligence, machine learning, and advanced software engineering. By the beginning of 2020, Kriegman had assumed the title of Director of Data Science and was leading a team tasked with implementing deep learning throughout the organization.

But within a few months, this would all collapse. A chain of eventsbeginning with the death of George Floyd and culminating with a statistical analysis of Black Lives Matters claimswould turn the 44-year-old data scientists life upside-down. By June 2020, as riots raged across the country, Kriegman would be locked out of Reuterss servers, denounced by his colleagues, and fired by email. Kriegman had committed an unpardonable offense: he directly criticized the Black Lives Matter movement in the companys internal communications forum, debunked Reuterss own biased reporting, and violated a corporate taboo. Driven by what he called a moral obligation to speak out, Kriegman refused to celebrate unquestioningly the BLM narrative and his companys diversity and inclusion programming; to the contrary, he argued that Reuters was exhibiting significant left-wing bias in the newsroom and that the ongoing BLM protests, riots, and calls to defund the police would wreak havoc on minority communities. Week after week, Kriegman felt increasingly disillusioned by the Thomson Reuters line. Finally, on the first Tuesday in May 2021, he posted a long, data-intensive critique of BLMs and his companys hypocrisy. He was sent to Human Resources and Diversity & Inclusion for the chance to reform his thoughts.

He refusedso they fired him.

I spoke with Kriegman just before Thanksgiving via Zoom. He dialed in from a small, cluttered room in his Jamaica Plain, Massachusetts home, where he lives with his wife and three children. He described his feeling of alienation, then frustration, then moral outrage, as he watched his Reuters colleagues behavior following the death of George Floyd. He described the company as a blue bubble, where people were constantly celebrating Black Lives Matter, where it was assumed that everyone was on board.

Like many corporations in the United States in 2020, Reuters went through a quiet revolution in human resources and diversity and inclusion. The company launched a series of lectures and training programs, ranging from a study of Kimberl Crenshaws intersectionality theory to an interactive panel called Lets Talk About Race to a keynote presentation on unlocking the power of diversity. In honor of Floyd, the company asked employees to participate in a 21-Day Racial Equity Habit-Building Challenge, which promoted race-based reparations payments, academic articles on critical race theory, and instructions on how to be a better white person.

Some of the materials were patronizing and outright racist. One resource told Reuters employees that their black colleagues are confused and scared, barely able to show up to work, and feel pressured to take the personal trauma we all know to be true and tuck it away to protect white people, who cannot understand anything beyond their own whiteness. The proper etiquette, according to a subsequent lesson, is for white employees to let themselves get called out by their minority colleagues and then respond with automatic contrition: I believe you; I recognize that I have work to do; I apologize, Im going to do better. The ultimate solution is for whites to admit complicity in systemic racism and repent for their collective guilt. White people built this system. White people control this system, reads a module from self-described wypipologist Michael Harriot. It is white people who have tacitly agreed to perpetuate white supremacy throughout Americas history. It is you who must confront your racist friends, coworkers, and relatives. You have to cure your country of this disease. The sickness is not ours.

Kriegman came to believe that the companys blue bubble had created a significant bias in the companys news reporting. Reuters is not having the internal discussions about the facts and the research, and theyre not letting that shape how they present the news to people. I think theyve adopted a perspective and theyre unwilling to examine that perspective, even internally, and thats shaping everything that they write, Kriegman said. Consequently, Reuters adopted a narrative that promotes a nave, left-wing narrative about Black Lives Matter and fails to provide accurate contextwhich is particularly egregious because, unlike obviously left-leaning outlets such as the New York Times, Reuters has a reputation as a source of objective news reporting.

A review of Reuters coverage over the spring and summer of 2020 confirms Kriegmans interpretation. Though early articles covering the first days of the chaos in Minneapolis were straightforward about the violenceProtests, looting erupt in Minneapolis over racially charged killing by police, reads one headlineReuterss coverage eventually seemed like it had been processed to add ideology and euphemism. Beginning in the summer and continuing over the course of the year, the newswires reporting adopted the BLM narrative in substance and style. The stories framed the unrest as a a new national reckoning about racial injustice and described the protests as mostly peaceful or largely peaceful, despite widespread violence, looting, and crime. More than 93% of recent demonstrations connected to Black Lives Matter were peaceful, Reuters insisted, even as rioters caused up to $2 billion in property damage across the country. The companys news reporters adopted the syntax of BLM activists. A May 8 story opened with the familiar say their names recitation, ignoring the fact that the first named individual, for example, had attacked a police officer, who was subsequently cleared of any wrongdoing: Michael Brown. Eric Garner. Freddie Gray. Their names are seared into Americans memories, egregious examples of lethal police violence that stirred protests and prompted big payouts to the victims families. Even as Seattles infamous Capitol Hill Autonomous Zone descended into lawlessness and saw the brutal murder of two black teenagers, the newswires headlines downplayed the destruction, claiming that the Seattle protests were diminished but not dismantled.

Reuterss data-based reporting and fact checks were also biased, always in favor of the BLM interpretations. One of the wire services special reports claims that a growing body of research supports the perception that police unfairly target Black Americans. They are more likely to be stopped, searched and arrested than their white compatriots. They also are more likely to be killed by police. In the 4,600-word story, Reuters gives only two short paragraphs to a dissenting viewpoint, then quickly dismisses it to advance the argument. In other stories, Reuters claims without evidence that Supreme Court protection of qualified immunity is rooted in racism, hosts an exclusively left-leaning panel on criminal-justice reform that uncritically promotes policies such as defund the police, and suggests that hundreds of unjustified police killings of black men fail to win victims any redress, without providing facts to substantiate the claim.

The companys data reporting consistently re-contextualized accurate information about racial violence and policing in order to align with Black Lives Matter rhetoric. In a fact check of a social media post that claimed whites are more likely to be killed by blacks than blacks are to be killed by whites, Reuters concedes that this is factually accurate but labels the post misleadingin part because it doesnt show that police kill black people at a higher rate than their share of the overall population, a completely unrelated claim. Likewise, when President Donald Trump accurately pointed out that police officers kill more white people than black people each year, Reuters immediately published a story reframing the narrative. Though the report admitted that half of people killed by police are white, the writers pushed the line that Black Americans are shot at a disproportionate rate and then used a quotation from the American Civil Liberties Union to paint the president as a racist.

Kriegmans decision to question his companys narrative wasnt sudden or impulsive. As he watched the riots and the news coverage unfold, he found himself increasingly filled with doubt and anxiety. He decided to take two monthsleave from Thomson Reuters in order to grapple with the statistical and ethical implications of the companys reporting on the riots and the Black Lives Matter movement. I did look through Reuterss news, and it was concerning to me that a lot of the same issues that I was seeing in other media outlets seemed to be replicated in Reuterss news, where they were reporting favorably about Black Lives Matter protests without giving any context to the claims that were being made at those protests [and] without giving any context about the Ferguson effect and how police pulling back on their proactive policing has been pretty clearly linked to a dramatic increase in murders, Kriegman told me. At a certain point, it just feels like a moral obligation to speak out when something thats having such a devastating impact is being celebrated so widely, especially in a news company where the perspective thats celebrated is having such a big impact externally.

During his leave, Kriegman used his skills as a data scientist to conduct a careful statistical investigation comparing BLMs claims on race, violence, and policing with the hard evidence from a range of academic and governmental sources. The result: a 12,000-word essay, titled BLM is Anti-Black Systemic Racism, that called into question the entire sequence of claims by the Black Lives Matter movement and echoed by the Reuters news team. I believe the Black Lives Matter (BLM) movement arose out of a passionate desire to protect black people from racism and to move our whole society towards healing from a legacy of centuries of brutal oppression, Kriegman wrote in the introduction. Unfortunately, over the past few years I have grown more and more concerned about the damage that the movement is doing to many low-income black communities. I have avidly followed the research on the movement and its impacts, which has led me, inexorably, to the conclusion that the claim at the heart of the movement, that police more readily shoot black people, is false and likely responsible for thousands of black people being murdered in the most disadvantaged communities in the country. Thomson Reuters, Kriegman continued, has a special obligation to resist simplistic narratives that are not based in facts and evidence, especially when those narratives are having such a profoundly negative impact on minority or marginalized groups.

Kriegmans essay focuses on debunking what he sees as the three key claims of BLM activists and their media supporters: that police officers kill blacks disproportionately, that law enforcement over-polices black neighborhoods, and that policies such as defund the police will reduce violence. First, Kriegman writes that the narrative about police officers systematically hunting and killing blacks is not supported by the evidence. For instance, in 2020 there were 457 whites shot and killed by police, compared to 243 blacks. Of those, 24 of the whites killed were unarmed compared to 18 blacks, he writes, citing the Washington Post database of police shootings. And though the number of blacks killed might be disproportionate compared with the percentage of blacks in the overall population, it is not disproportionate to the level of violent crime committed by black citizens. Depending on the type of violent crime, whites either commit a slightly greater (non-fatal crimes) or slightly smaller (fatal, and serious non-fatal crimes) percentage of the total violent crime than blacks, but in all cases roughly in the same ballpark, Kriegman writes. However, according to the Justice Departments National Crime Victimization Survey data, there are many more whites killed by police, even though whites account for a similar absolute number of violent offenders. Thus, if the number of potentially violent encounters with police reflects the violent crime rates, then the raw statistics suggest that there is actually a slight anti-white bias in police applications of lethal force. To round out his case, Kriegman concludes with a study by Harvards Roland Fryer, which, according to Fryer, didnt find evidence for anti-Black or anti-Hispanic disparity in police use of force across all shootings, and, if anything, found anti-White disparities when controlling for race-specific crime.

Next, Kriegman takes up over-policing. Black Lives Matter activists and Reuters reporters had pushed the idea that police officers focus disproportionate attention on black neighborhoods and, because of deep-seated racial bias, are more likely to stop, search, and arrest black Americans than their white compatriots. While this might be true on its face, Kriegman writes, it misses the appropriate context: black neighborhoods are significantly more violent than white neighborhoods. If police want to reduce violent crime, they must spend more time in the places where violent crime occurs. Kriegman points out to his colleagues in Thomson Reuterss Boston office that the reason that police have more confrontations in predominantly black neighborhoods in Boston is because that is where the great bulk of violent crime is occurring, with nearly all the annual murders happening in predominantly black neighborhoods such as Dorchester and Roxburyfar from the homes and offices of his colleagues in the professional-managerial class at Reuters. And Boston is hardly an outlier. According to Kriegman, the most rigorous statistical analyses demonstrate that violent-crime rates and policing are, in fact, highly correlated and proportionate. He quotes a Justice Department report which found that for nonfatal violent crimes that victims said were reported to police, whites accounted for 48% of offenders and 46% of arrestees. Blacks accounted for 35% of offenders and 33% of arrestees. Asians accounted for 2% of offenders and 1% of arrestees. None of these differences between the percentage of offenders and the percentage of arrestees of a given race were statistically significant.

Finally, Kriegman addresses the policy implications of de-policing. Contrary to Reuterss sometimes glowing coverage of the defund the police movement, Kriegman makes the case that de-policing, whether it occurs because of the Ferguson Effect or because of deliberate policy choices, has led to disaster for black communities. His argument, building on the work of City Journals Heather Mac Donald, follows this logic: after high-profile police-involved killings, such as those involving Michael Brown in Ferguson, Missouri, and George Floyd in Minneapolis, Minnesota, the Black Lives Matter movement and the media have demonized police departments and caused many officers to reduce proactive policing measures and to pull back from situations out of fear that they might need to use force. The result, according to data from a range of academic literature, is an increase in crime and violence. Kriegman again cites Fryer, who concluded that the Ferguson Effect led to 900 excess murders in five cities he considered, and the University of Utahs Paul G. Cassell, who found that the Minneapolis Effect led to 1,520 excess murders in the United States. Thus, BLMs signature policy solutiondefund the policewould likely lead to incredible carnage in black communities.

Kriegman hoped that his essay would help his colleagues move beyond the blue bubble and see how devastating Black Lives Matter has been to black communities, which would in turn help them to do more accurate and responsible journalism. Returning from leave, he was ready to share his research with his colleagues at Thomson Reuters. I didnt know what to expect going into it, but I expected the reaction to be intense, Kriegman says. And it was. The essay dropped like a bomb on Reuterss internal discussion forum, called The Hub. According to Kriegman, content moderators immediately took down the post and called in a team of HR and communications professionals to manage the situation. They told Kriegman that they were reviewing the document but, according to Kriegman, failed to provide specific objections to what he wrote. The essay, while challenging the dominant left-wing culture at Thomson Reuters, made a reasoned, dispassionate case based on rigorous evidenceprecisely what a hard news organization should prioritize internally. Finally, after Kriegman inquired multiple times about the companys decision to remove the post, senior human resources director Melissa Budde told him that the post was too antagonistic and provocative and that he needed to work with Cristina Juvier, head of diversity and inclusion, if he wanted to pursue the matter further.

Over the next two weeks, Kriegman went through a gauntlet of calls, meetings, and chat conversations, hoping that he could revise the essay to the satisfaction of the various parties. In all these conversations, Kriegman maintains, the human resources and diversity-and-inclusion employees never offered substantive critique of his piece; they always retreated to vague concerns about tone and the belief that it would offend BLM supporters within the company. The transcripts of the calls and emails from May 4 and May 27, 2021, show a steady escalation of hostilities. Kriegman insisted that he be allowed to repost the essay. Two of his colleagues warned him that he was potentially heading toward disaster; another, according to Kriegman, screamed that he should fucking do [his] job instead of spending time fighting about Black Lives Matter. (None of the Reuters employees returned a request for comment.)

On May 28, after incorporating some of the feedback on tone from human resources, Kriegman reposted his essay under a new title: BLM Spreads Falsehoods That Have Led to the Murders of Thousands of Black People in the Most Disadvantaged Communities. This time, the moderators at The Hub let it stay up. Kriegman considered this a victoryand then the comments started flooding in. They began politely, but soon descended into open hostility. Wow, this is incredibly inappropriate for a professional website, wrote commercial transactions intern Kasia Guzior. Your premise in the what about both sides sort of question youre asking here is that its a political question. That premise is incorrect; its a human rights issue . . . Statistics and facts have been used to support racist actions for at least all of US history, said tax analyst Abbie Gentry. The FBI put out an article (look it up) a couple of years ago, stating that Law Enforcement organizations have been infiltrated by white supremacists the likes of the KKK. If some law enforcement officers are white supremacist Klan members, is it a surprise when they target and kill disadvantaged black people? asked another commenter. As a white person I am embarrassed and ashamed for you. We, as white folks, should NEVER presume to speak for people of colorwhich is what youve chosen to do, concluded premier digital marketing strategist Joanne Fleming. White folks trying to help by whitesplaining how and why a movement that does not belong to us is harming people of color only does further harm.

Five days later, Thomson Reuters made the decision permanently to remove the post from the companys internal servers. Kriegman accused his colleagues of creating a hostile work environment and attempted to complain to that effect on the discussion board; he was then suspended from The Hub and locked out of email and other communications platforms. In a final, grand, and perhaps self-immolating gesture, Kriegman personally emailed Thomson Reuterss top executives, complaining about the companys bias and hostility toward his criticism of Black Lives Matter. And then they went ahead and fired me, Kriegman told me. I was expecting it. It didnt come as a great surprise that they ended up firing me. The final email from Melissa Budde hit with a thud: The manner in which youve conducted yourself in recent weeks does not align with our expectations for you as a leader within Thomson Reuters, she wrote. It was over. Six years as a data scientist, dozens of high-profile projectsall set ablaze out of a deep frustration about the falsehoods Kriegman felt were ruining the newsroom.

More than half a year after his firing, Kriegman is reflecting. He assures me that he and his family are in a comfortable financial situation, thanks to some early investments in Bitcoin and tech stocks. I have three kids, and Ill be completely honest. I would not have headed down this road if I thought it was going to have a devastating impact on my family. I was expecting that this would be one of the possibilities. . . . I was hoping for a different possibility, but I certainly knew that this was a chance. Through a Zoom window, he comes across as rational, intelligent, and mathematically minded, if somewhat lacking in social graces. Perhaps he was nave to believe that data and evidence would convince his colleagues that they were in the grip of a false narrative; perhaps he failed to understand that politics is not a rational science and that his colleagues would perceive his essay as a flagrant transgression. When I ask him how he feels after the ordeal, he laughs: You want me to talk about my emotions? I cant even talk about my emotions to my wife.

Still, Kriegman is genuine in his concern and sees a broader lesson in his experience. Im extremely disturbed by whats happening in our country, he says. Its absolutely clear that in our major news organizations, people are not discussing these issues openly. They cant afford to. Theyll be fired. He believes that critical race ideologies, adopted wholesale by the professional-managerial class, have become entrenched within American institutions. He tells me that the new racial orthodoxy is slowly creeping into every aspect of daily life, from the Reuters newsroom to his sons elementary school classroom, which has been teaching a book called Race Cars, a story depicting a committee of white race cars that conspires to make sure no black cars win the big race. Its absolutely poisonous to the country, he says.

Was it worth it? I feel proud of what I did, but I dont feel satisfied that I had a big impact within the company, Kriegman says. I dont think that it changed anything. He lost his job at Reuters, but more than that, he lost almost all his friends there, too. My closest friends have abandoned our friendships, he says. Only two of the people that Id actually worked with reached out to me and said, How are you doing? And neither of them were the people that I was closest with. Kriegman is now contemplating his next steps. He can afford to take some time away from work, but he fears that his once-golden rsum has sustained damage. I suspect that if Im honest about how I left my last job, it would be difficult to ever find another job, he tells me.

Kriegman follows in the footsteps of people like James Damore, Bari Weiss, Nellie Bowles, Jodi Shaw, and Paul Rossi, who found themselves unable to live honestly within the confines of Americas elite institutions. Like those other dissenters, he has immense talents that he could apply to the cultural and political problems facing our country. I hope that he does so. I also hope that one day, his former colleagues at Reuters see that, while Kriegman might have been a little abrasive, he was ultimately right. If the wire services continue to promote myths about race, violence, and policing, they will inflict grave harm on their reputations for fairness; they will also help unleash a new wave of destruction in Americas poorest and most vulnerable neighborhoods.

Christopher F. Rufo is a senior fellow at the Manhattan Institute and a contributing editor of City Journal. Sign up for his newsletter here.

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BLM, Reuters, and the Price of Dissent - City Journal

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Schnucks’ Data Solutions Exec Promoted to Strategy Team – Progressive Grocer

Schnuck Markets Inc. has promoted Chief Data Officer and Deputy CIO Tom Henry to serve on the companys strategy team, effective immediately. In this role, Henry will expand on his current leadership role to execute strategic initiatives that support the companys mission.

Tom is not only well known in his area of expertise, but also continues to demonstrate a proactive approach to shape our competitive landscape, said Todd Schnuck, chairman and CEO of Schnucks. His intense focus on Nourishing Peoples Lives, combined with his creativity and curiosity, make him a valued leader for our strategy team and our company.

Since joining Schnucks in 2019, Henry has led the development of the companys data and analytics organization, which provides unique and actionable insights to each of Schnucks business units. He has been the companys chief data officer and deputy CIO since May 2021. Henry joined Schnucks from Express Scripts Holding Co., where he used his deep understanding of business intelligence and data analytic strategies to position Express Scripts among the health care industrys leaders in the delivery of data-driven insights and advanced analytic solutions.

Henry earned a bachelor of science in computer information systems from Missouri State University, where he graduated magna cum laude. He is the global chief data officer ambassador for Missouri and serves as a board member for the Washington University and the University of Missouri data science programs, where he shares his knowledge with both faculty and students. Henry is also a national VP for the Muscular Dystrophy Association.

Ive enjoyed collaborating with my Schnucks teammates to create data solutions that help us to better serve our Schnucks customers, said Henry. Im honored to take this new leadership role and look forward to expanding my scope of responsibilities within the company.

Schnucks recently introduced GetUpsides cashback solution at all of its stores. Shoppers can use the free GetUpside mobile app to take advantage of personalized cashback promotions. Instead of snapping and submitting apicture of a receipt, shoppers can just click Check in and GetUpside will verify each transaction.

St. Louis-basedSchnucksoperates 111 stores in Missouri, Illinois, Indiana and Wisconsin, and employs 13,000 associates. The company is No. 64 on The PG 100, Progressive Grocers 2021 list of thetop food and consumables retailers in North America.

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12 in-demand technical hires leaders want to make in 2022 – Fast Company

Tech talent is in high demand these days. Across various industries, youll find companies are competing with one another for the top tech talent to help them grow their business.

Looking ahead to 2022, many companies have already begun planning and are hoping to recruit more employees in the new year. Below, 12 Fast Company Executive Board members share the No. 1 technical hire their company is looking to make in 2022.

1. DIGITAL TRANSFORMATION SPECIALIST

As more organizations look to embrace the benefits of digital transformation, were seeking talent that understands how to help customers make this transition possible. Helping them adopt digital services and the cloud is critical, and we need people who can provide support and guidance along this journey. In todays business environment, digital transformation is a necessity, not an option. Matthew Tengwall, Verint Systems

2. CHIEF TECHNICAL OFFICER

We plan to hire a CTO who is focused not on building a technology platform, but on how to best leverage and integrate a lot of existing platforms. Unless you are a software company, you really should not have to build much from scratch these days. Someone who knows how to integrate existing platforms is very valuable because they can really accelerate growth. Alex Husted, HELPSY

3. TECHNICAL PROJECT MANAGER

Addressing technology concerns, a project manager can improve all aspects of project planning and resource management. Their technical prowess and inspiring leadership make them adept at working in a collaborative environment, driving strategy, and delivering desired results for scheduled projects. Irfan Khan, CLOUDSUFI

4. DATA ENGINEER

A high-performing team should have 10 data engineers to everyone data scientist. Data engineers dig out the data, clean the data, and prepare the data for analysis. Meagan Bowman, STOPWATCH

5. FULL-STACK DEVELOPER

Full-stack developers are always in high demand. Add in data science to the mix and it is a dangerous combination. In 2022 and beyond, it will be hard to run any company without either of them. Joseph DeWoody, Valor Mineral Management

6. VP OF RESEARCH AND DEVELOPMENT

We will hire a VP of research and development. Were growing fast and need to start supporting dozens and dozens of enterprise and SaaS clients that are quickly turning into hundreds. Yoav Vilner, Walnut

7. TEAM OF DEVELOPERS

My company will be building out our developer team to provide support for current applications and the development of new add-ons to continue company growth. This team most likely will be remote and could very well be spread out internationally. We are focused on talent and skills more than location. Martin Rowinski, Boardsi

8. CYBERSECURITY ANALYST

This is not on an immediate basis but a cybersecurity analyst can be a candidate since hackers are becoming more and more sophisticated these days. I believe that all categories of data must be protected from damage. This includes any level of threats that are being used in unlawful situations. Lane Kawaoka, SimplePassiveCashflow.com

9. TECH PROFESSIONALS WITH MARKETING EXPERIENCE

As my business grows, it becomes necessary to hire tech professionals who know their way around marketing. Today, it simply isnt enough to know how to build a product. You also need to know who youre building it for and how to make it easy for them to use. Data analysts, growth marketers, and others who have tech expertise are valuable assets to a growing business. Syed Balkhi, WPBeginner

10. DATA SCIENTISTS AND MATHEMATICIANS

Data scientists and mathematicians will be a key focus for us in 2022 in order to expand our product offering within our industry. The blend of statistical analysis and mathematics is crucial in a data-tech organization. Additionally, privacy specialists will be a key focus as legislation continues to evolve surrounding the protection of personally identifiable information. Amanda Dorenberg, COMMB

11. TECHNICAL PRODUCT MANAGER

We will continue to build security, data, and platform teams in 2022. A technical product manager is our No. 1 hire. This role would lead our aggressive focus on security (we recently received SOC2 Type 1 Certification) and expand our security team while broadening our capabilities. Cody Barbo, Trust & Will

12. OUTSOURCED LOW-CODE PLATFORM

Unless you are a technology company, tech is best outsourced. A lot can be done by business users with minimal-coding platforms. Every non-tech company should make a decision on such a platform and empower its business users. When it comes to any specialization, I recommend leaders to retain fractional experts who will supercharge the business. Pawan Mehra, cKinetics Inc

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AIM announces the fourth edition of The Rising, India’s Biggest Women in AI Conference – Analytics India Magazine

Analytics India Magazine has now announced the fourth edition of the coveted The Rising (powered by Fractal) event. The event aims to bring together some of Indias brightest women data scientists and will be held in person on April 8 in Bengaluru, Karnataka. For the last three years, The Rising event has gained the reputation of being the biggest and one of its kind meeting of women data scientists leaders across boards, exchanging ideas and serving as an inspiration for other women for participating in STEM.

Some of the leading visionaries will share their perspectives on building a sustainable and successful career in the ever dynamic world of data science. The event will host a range of talks and information sessions that would greatly help women develop leadership skills. While The Rising focuses on women data scientists, it is open to all. People willing to network and participate in the discussions around AI and leadership are more than welcome.

The event is expected to host 250 attendees and feature over 15 talks from industry mavens; this is apart from informal sessions dedicated to inspiring more women to join the STEM fields. As a participant, you would also get to meet more than 100 leading companies striving hard to build a more inclusive industry.

To get more information and book your tickets, visit this link.

One of the foremost benefits of attending The Rising event is the opportunity to interact with experts and enterprises who have a strong presence in the data science field. For many, this could be a good chance to pitch their portfolios and resumes to the companies participating in the event. The Rising 2021 event saw representatives from leading companies like Google, NetApp, Philips, and Deloitte in attendance.

Participants will also get to attend insightful tech talks that will detail various industry use cases that the speakers might have worked on over the course of their careers. These insights may help the attendees in sailing smoothly through the current challenges they may be facing at their work/projects.

Apart from the tech talks, The Rising event will also have a few workshops on trending topics of AI and data science. These workshops will be conducted by domain experts that would expose the participants to the latest trends and introduce them to tools and techniques to solve their tech challenges.

The most important aspect of the event is also the most intangible one. The Rising event has and would continue to spark a conversation on gender imbalance in tech, more specifically in the data science field. Leading and driving the conversation forward would be the industry trailblazers, most of whom have played active roles in promoting inclusivity in their fields.

Thats not all. As a token of appreciation and recognition for their work, The Rising event will also host the Women in AI leadership awards. Through this award, we celebrate the technology leaders who have had an incredible impact in the tech community.

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What does the future of tech education look like? – Siliconrepublic.com

National College Irelands Anu Sahni discusses the changes in how tech education is delivered and what students need to know.

The education sector, like many others, have undergone a lot of change due the advancements in technology. The way students, graduates and employees learn and upskill has changed due to developments in online learning and this has become more prevalent in the last two years due to the pandemic.

However, the changes in the tech landscape have also impacted the skills that are most in-demand and in turn have expanded the courses and education options for those interested in a career in tech.

The growing demand for tech workers and specialised skills has led to both education bodies and industry players offering a range of tech courses.

In the last year alone, University of Limerick teamed up with tech companies to develop an immersive software engineering programme, Microsoft Ireland added a cloud skills programme to its list of free courses and UCD partnered with global analytics company SAS to provide a free online skills programme, which includes data science.

In June 2021, more than 10,000 places on almost 300 courses in Ireland were announced under Springboard+, an upskilling initiative in higher education that offers free and subsidised courses.

The expansion of digital skills is a great sign for the tech industry and helps thousands of students, employees and jobseekers upskill in new and evolving areas of tech, but how all this change affecting the education and training sector?

Anu Sahni is the programme director for the MSc/PGDip in data analytics ad National College Ireland (NCI).

Outside of her work on the data analytics curriculum, Sahni also organises hackathons and inventathons within the college so that students experience the process of developing an idea with input from experts and the rigour of pitching to industry.

Sahni told SiliconRepublic.com that technology has became a major tool in terms of pedagogical resources in education and training.

Technology has made the connection of theory with the real world stronger. Easy access to online resources, communities and social media has made projects and assessments more practical and real-world oriented. For technology students, practical tasks such as coding, projects, problem-solving, research, surveying, data analysis, etc., have become more important compared to theory-focused, essay-type, written exam-based assessment.

Its this need for practical, hands-on experience that can change how people are educated when it comes to tech. However, a balance with theoretical or academic learning is still needed in tech, so that students can apply it to a wide range of areas in everything from autotech to healthcare.

The theoretical concepts should be demonstrated, validated, taught and exemplified by hands-on experience. The assessments should then be based on testing students comprehension and application in solving a real-world problem, said Sahni.

The theoretical concepts should ideally be supported and exemplified by practical work before moving onto the next theoretical concept. The teaching of theoretical concepts should be illustrated with real-world examples.

In terms of how technology has changed education itself, Sahni points to advancements in simulation, 3D modelling and visualisation, all of which have led to a better understanding of theoretical concepts.

For example, there are 3D models and simulations of human anatomy available that make it easy for medical students to visualise the concepts learned in theory without having to do dissections.

However, while a more dynamic education is of great benefit to students, it can also come with its own challenges as the technical content has to be regularly updated.

Documentation sometimes lags quite far behind the changes that have taken place in the software, so students have to rely upon the forums and community to stay ahead, said Sahni.

Sahni said the tech education industry in Ireland is keeping good pace with the fast growth of the industry itself, especially with the growing number of third-level institutions offering courses in areas such as AI, data analytics, cybersecurity and AR/VR.

There are many free resources, forums and communities that learners can leverage. There are many successful initiatives that are bridging the gap between industry and academia.

As part of the NCI data analytics course, students competed in Enfuse, a Dublin City Council and Local Enterprise Office initiative.

The Enfuse competition matches enterprises and social enterprises in Dublin with masters students, with the student teams presenting solutions to address the challenges these enterprises face.

Sahni said there should be more schemes like this. There should be repositories, similar to libraries, where learners can find the latest tools, devices, software, etc., for conducting experiments and collaborating with experts. There are certain labs, such as CeaDAR, but they are largely limited to the institutes where they are based.

For tech students looking to progress their career, Sahni said dont be afraid of using new tools and technologies.

Let your imagination and passion go wild. Get a good grip of theoretical concepts and whats going on underneath the hood. No concept is fully clear without hands-on experience, therefore practice, research, collaborate, innovate and explore, she said.

Dont hesitate to reach out to educators, other learners and experts, they are more welcoming than you expect. Before you implement or invent something new, judge the impact on society carefully, not only in present but in future too everything should be ethically and morally right. For data science students, respect privacy.

Applications for NCIs Springboard+ and Human Capital Initiative courses starting in January 2022are now open, with courses in areas such as data analytics, cybersecurity, software development and artificial intelligence.

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Domino Data Lab Named a Winner of Built In’s Best Places to Work Award for Second Year in Row – PRNewswire

SAN FRANCISCO, Jan. 6, 2022 /PRNewswire/ -- Domino Data Lab, provider of the leading Enterprise MLOps platform trusted by over 20% of the Fortune 100, today announced that Built In has selected it for several of its 2022 Best Places to Work Awards. Following the data-backed selection process, Domino has been honored in Built In's San Francisco lists of Best Places to Work, Best Midsize Companies to Work For, and Best Paying Companies.

Domino continues to earn praise for its employee satisfaction and the quality of its workplace culture and benefits. Headquartered in San Francisco with a global workforce, this is the second consecutive year Domino has been named by Built In as one of the Best Midsize Companies and Best Paying Companies to work for in San Francisco.

"Each member of our team comes from a unique background and has different experiences which help us foster an environment of creativity and problem solving," said Nick Elprin, CEO and co-founder of Domino Data Lab. "This culture promotes our team's devotion to customers and helps us deliver results to the most sophisticated companies in the world."

Built In determines the winners of Best Places to Work based on an algorithm, using company data about compensation, benefits, and companywide programming. To reflect the benefits candidates are searching for more frequently on Built In, the program also weighs criteria like remote and flexible work opportunities, programs for DEI, and other people-first cultural offerings.

"It is my honor to extend congratulations to the 2022 Best Places to Work winners," says Sheridan Orr, Chief Marketing Officer, Built In. "This year saw a record number of entrants and the past two years fundamentally changed what tech professionals want from work. These honorees have risen to the challenge, evolving to deliver employee experiences that provide the meaning and purpose today's tech professionals seek."

Domino is hiring! If you want to join our award-winning team and make a mark on data science to solve the world's most important problems, we are hiring here in San Francisco, New York City, Boston, London, and remotely for select roles. Learn more about our career opportunities here.

About Domino Data LabDomino Data Lab powers model-driven businesses with its leading Enterprise MLOps platform that accelerates the development and deployment of data science work while increasing collaboration and governance. More than 20 percent of the Fortune 100 count on Domino to help scale data science, turning it into a competitive advantage. Founded in 2013, Domino is backed by Sequoia Capital and other leading investors. For more information, visit dominodatalab.com.

About Built InBuilt In is creating the largest platform for technology professionals globally. Monthly, more than three million of the industry's most in-demand professionals visit the site from across the world. They rely on our platform to stay ahead of tech trends and news, develop their careers and find opportunities at companies whose values they share. Built In also serves 1,800 innovative companies of all sizes, ranging from startups to the Fortune 100. By putting their stories in front of our uniquely engaged audience, we help them hire otherwise hard-to-reach tech professionals, locally, nationally or remotely.www.builtin.com

About Built In's Best Places to WorkBuilt In's esteemed Best Places to Work Awards, now in its fourth year, honor companies across numerous categories: 100 Best Places to Work, 50 Best Small Places to Work, 100 Best Midsize Places to Work, 50 Companies with the Best Benefits and 50 Best Paying Companies, 100 Best Large Companies to Work For, and 50 Best Remote-First Places to Work.

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Council Post: Building the next generation of AI professionals – Analytics India Magazine

Artificial intelligence (AI) has moved from being a niche topic to a dominant technology. With rapid advancements, AI has been creating massive business opportunities and breakthroughs, prompting leaders to invest more in it. With an increased demand for AI capabilities, the demand for skilled individuals working in this field has also skyrocketed. If someone wants to dive into the field of AI and data science, this would be the best time to do so. A career in AI is rewarding and exciting, and the field is full of opportunities. This article could be a good guide to people looking to build a career in this field.

Like every career, there are different roles in the workplace, and its important to familiarise oneself with them. In AI parlance we have roles starting from business translators, data engineers, and data scientists to BI developers, Model Ops engineers, and project managers, etc. Depending on your area of interest, you can build your career as you move along. Careers are no longer narrowly defined by a specific title and a set of skills tied to it.

In the ever-changing environment, having a T-shaped career can make it easier to adapt. Used in-house at McKinsey & Company for the first time, this is also sometimes referred to as a Generalised Specialist profile. The vertical bar on the T-shaped person depicts an individuals unique abilities and how deep their knowledge is. The horizontal bar shows the persons ability to use the available skills and capabilities to collaborate with others in different areas of expertise.

There are three dimensions to what enterprises generally look for in an AI professional mindset, skillset, and toolset. The mindset translates the ability to understand the requirement and converts it into a problem-solving framework. This is essential to understand the business context or the domain part of it. Next is the skillset, which focuses on the primary skillset and explores your horizontal capabilities to find the best solution. If you can think in terms of where you can utilise a part of the solution to address another different issue that has similarities in nature, you then create unique, anomalistic solutions. And the last part is the Tool Set, or the technology part, which helps in translating the thought process into a realisable solution the application part. How you capture all three pieces ultimately determines your success as an AI professional.

Technology is advancing at a rapid pace; leveraging new technology saves time and money while improving final output results. Everyone learns and consumes information differently; here are some of the best ways to start learning and keeping up with technology:

Conventional learning alone will not suffice. There is a need to accelerate learning and skills development in data science and AI and make it available to a large number of aspiring learners.

Data science and AI have become all-pervasive across functions and industries. Up to 90 per cent of small, mid-size and large organisations have developed advanced analytics capabilities to stay relevant in the market. They use these capabilities to build analysis models, simulate scenarios, and predict future trends. AI and data science-related jobs will continue to grow in the coming years.

This article offers broad insights on what to look for in a career in AI; its time to make that move and get started on your learning curve. One can only hope to progress in a career if there is constant value addition. The key is to be confident in your skillset, communication and networking skills, and being a team player.

Happy Learning.

This article is written by a member of the AIM Leaders Council. AIM Leaders Council is an invitation-only forum of senior executives in the Data Science and Analytics industry. To check if you are eligible for a membership, please fill the formhere.

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Video Career Paths in Analytics and Data Science and Analytics Team Building Machine Learning Times – The Predictive Analytics Times

Event:Machine Learning Week 2021 Keynote:Career Paths in Analytics and Data Science and Analytics Team Building Speaker:Meghan Anzelc, Head of Data & Analytics, Spencer Stuart Bio: MeghanAnzelcHeadofData&AnalyticsMeghanjoinedSpencerStuartin July 2018 leadingdataandanalyticsfor the firm. She is responsible for creating and implementing a strategy and roadmap to advance thedataandanalyticscapabilities acrossSpencerStuart, focusing on delivering greater impact to our clients and for the firm. Career Paths in Analytics and Data Science and Analytics Team Building: In this talk Dr. Anzelc will provide an overview of her own career path from particle physics PhD to insurance analytics executive to people analytics leader, providing a view

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Ses-imagotag : SES-imagotag completes the acquisition of Irish data analytics start-up MarketHub with founder Roy Horgan to join SES-imagotags…

SES-imagotag completes the acquisition of Irish data analytics start-up MarketHub with founder Roy Horgan to join SES-imagotag's executive team

SES-imagotag, (Euronext: SESL, FR0010282822) the global leader in IoT solutions and smart labels for physical retail, deepens its investment into intelligent retail by completing the 100% acquisition of Irish data analytics start-up MarketHub Technologies Limited. With its founder Roy Horgan to join the SES-imagotag global executive team as Group SEVP of Strategy, Marketing and Communications.

SES-imagotag has held a majority holding in the Irish retail analytics start-up since 2019 and is delighted to announce the 100% acquisition of the remaining shares of MarketHub with immediate effect.

Group Chairman and CEO Thierry Gadou welcomes the MarketHub founder Roy Horgan and team to the SES-imagotag group where they will be responsible for further developing a data center of excellence from their headquarters at Cork, Ireland.

Thierry Gadou, Chairman and CEO of the SES-imagotag group comments: As SES-imagotag continues to scale its VUSION Retail IoT Cloud platform across its 30,000 stores, the MarketHub acquisition further develops our presence in retail data science and helps extend the range of disruptive technologies connected to the VUSION platform. The numerous synergies between our solutions will strengthen our leading position in the convergence of physical and digital retail.

Roy Horgan, Founder and CEO of MarketHub concludes: At MarketHub, it is our belief that every store underperforms. We created the vision of the self-learning store where stores can become agile, smarter, and adapt. Joining SES-imagotag allows us not only to be part of one of Europe's fastest growing technology companies, but to also scale our data-led insights to unprecedented levels. On a personal note, I am also excited and energized by joining the SES-imagotag family; this is a great outcome for both companies.

About SES-imagotag and the VUSION Retail IoT Cloud platform

SES-imagotag is a fast-growing retail tech company, listed on the Euronext Paris stock exchange, with revenues of290 million. The company is the world leader in smart digital labels and IoT solutions for physical retail, serving over 300 large retailers around the world in Europe, Asia, and America.

SES-imagotag has developed the VUSION Retail IOT technology platform to help retailers transform their physical stores into high value digital assets, more automated, data-driven, and connected in real-time to suppliers and consumers. VUSION improves pricing agility, accuracy, and integrity; enables omni channel synchronization of prices, product information and marketing content; and increases the productivity of shelf replenishment and in-store picking for online orders. VUSION improves employee satisfaction by freeing up time from cumbersome low value-added tasks and allows them to focus on customer service and merchandizing tasks. VUSION connects shelves to the cloud, providing real-time accurate information on product availability and location, allowing for reduced inventory, out-of-stock, and waste, as well as improved on-shelf availability and merchandizing compliance.VUSION empowers consumers with better product, nutritional and traceability information at the shelf and enables a frictionless in-store shopping experience with features such as product search, pathfinding and cashier-less scan & pay features.

http://www.ses-imagotag.com

Ticker symbol: SESL ISIN: FR0010282822 Reuters: SESL.PA Bloomberg: SES SES-imagotag is listed in compartment B of Euronext Paris

Contact

SHAN - Investor Relations and Financial Communications

Alinor Kuentz: Tel: +33 (0)1 42 86 82 45 / sesimagotag@shan.fr

2022 ActusNews

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