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(US and Canada) Nicolas Chaillan, Chief Technology Officer, Prevent Breach, speaks with Michael C. Fillios, Founder and CEO, IT Ally, about his experience of working in public versus private sectors, incorporating DevOps and DevSecOps, and the three-pillar approach to cyber-security.

Chaillan introduces himself as the youngest French entrepreneur who made a difference by applying his cyber innovation skills to national security. First, he joined the Department of Homeland Security as the special advisor for cyber and chief architect. Then Chaillan was appointed the first Chief Software Officer at the Department of Defense.

The transition from being the founder of a smaller start-up to the bureaucratic universe of DOD was mind-boggling, he says. As an entrepreneur, he had the power to control and get things done. But with a massive team of 4 million people with annual funding of 810 billion in the Department of Defense, it felt staggering, says Chaillan.

Next, he mentions that some silos and barriers came in the way of executing the job at DOD, but the sense of honor from serving the nation remains unmatched. Chaillan reckons that one can become a part of the problem by not realizing when to go back to the commercial side.

Chaillan considers DevOps a massive enabler that saved them 100 years’ worth of time when they moved 27 heavy-duty programs into it. Then, he highlights the importance of incorporating the innovative tools of DevOps and DevSecOps at a government agency. The methodology removes the silos and barriers between the development and operation teams while delivering incremental software multiple times a day, affirms Chaillan.

With DevOps, the organization will know where to focus and witness a rapid return on investment, Chaillan continues. He emphasizes failing fast but not failing twice for the same reason.

Moving on to DevSecOps, he maintains that it is an evolution of DevOps, which weaves security into every stage of software development. Chaillan analogizes DevSecOps as a weapon to orchestrate the entire stack of software that is running while augmenting the cyber capabilities of an organization.

In this context, Chaillan highlights three pillars of cyber-security. The first is moving target defense, wherein the software is transient and must be brought to an immutable state every four hours. He asserts doing numerous things like that to mitigate the ability of the malicious actor to access the software stack.

The second pillar of modern cyber defense is zero trust, where access is denied based on well-defined policies. It prevents the threat actors from accessing a part of the system and prohibits their lateral movement to access crown jewels.

Finally, Chaillan explains the third pillar, in which continuous monitoring of system behavior through AI and ML happens. Here the system is monitored, and if it misbehaves, they remove the misbehaving capability to ensure the system returns to its desired state.

[This content was originally published on cdomagazine.tech.]

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(US and Canada) Brad Burke, Chief Engineering and Data Officer, American Family Insurance, speaks with Michael C. Fillios, Founder & CEO, IT Ally, about gathering and analyzing data for optimizing marketing decisions, data privacy, how SMBs grow with technology, and how the intersection of data engineering and software engineering advances data science.

Burke recalls being involved in marketing tech start-ups when the big data revolution was underway. He says the usage of analytics demanded leveling up to unlock masses of data. Machine learning and data science came in, followed by cloud migration.

Next, he states that respecting the consumer is fundamental. With the internet becoming more social and people posting unstructured content, they worked on various platforms to understand dos and don’ts with data, says Burke. Classifiers had to be put in place to understand millions of conversations happening in a day.

From a technology perspective, says Burke, it boils down to understanding how to scale a massive data pipeline and organize the records in real-time. He affirms that analytics is the primary use case for collecting and organizing information at a massive scale.

Speaking about data privacy, Burke mentions that the past processes of collecting information were not ideal. He maintains that data is the gift of a consumer and must be respected.

He highlights that it is the time for small and medium-sized businesses to shine with the available technologies. Cloud is amazingly transformative, he continues, but the company needs to be customer-centric and think of it holistically. He further notes that understanding the security posture and having a good security partner go a long way in the journey.

Burke emphasizes how data engineering becomes like software engineering with cloud capabilities. With the current technologies, one can be more iterative with data, and the developmental capabilities look more like software engineering. He recalls developing SAP software in the ‘90s when they could not afford to make a mistake with a $1 million warehouse.

He stresses the need to have data engineering and software engineering capabilities to activate data science. Burke believes that these domains must work in concert to create a product.

[This content was originally published on cdomagazine.tech.]

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(US and Canada) Jennifer Bachner, Director, Data Analytics and Policy Program, The Johns Hopkins University (JHU), speaks with Michael C. Fillios, Founder & CEO, IT Ally, about preparing students for opportunities, transformation for SMEs, and congressional redistricting.

Bachner says that students with a substantive area of interest or expertise are best prepared to do well in their careers. She mentions that students taking the courses at JHU become experts at using a variety of sophisticated statistical techniques and can apply the most appropriate method to a particular policy or governance challenge. They also have a passion for solving real-world problems and for analytics.

It’s impossible to conduct a strong analysis without a firm understanding of the issues at hand, adds Bachner. She encourages her students to continue developing their knowledge while in the program so that they can use it to make good judgments when performing analytics.

Bachner goes on to share advice for small businesses on their approach to using data to prepare and grow their business for the future. She highlights four key suggestions:

  • Create an enterprise analytic strategy.

  • Implement self-service models.

  • Focus on communication when developing their analytic teams.

  • Start thinking about how they can leverage AI and machine learning tools in the future.

She also advises organization leaders to think about new approaches to education and training for their staff in the area of data literacy.

Speaking on using data and analytics to inform congressional redistricting, Bachner mentions that among the key challenges is agreeing on a criterion for defining a good versus a bad congressional district.

[This content was originally published on cdomagazine.tech.]

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(US and Canada) Anthony Mazzarella, Director of Data Governance, Voya Financial speaks with Michael C. Fillios, Founder & CEO, IT Ally, about IT capabilities for SMBs, skills of a change agent, and team building. He starts by acknowledging the people and the relationships that propelled his career.

Mazzarella says that companies need a champion to start raising awareness around the value of IT capabilities SMBs can leverage. They don’t need to pay for expensive tools, rather use open source tools. He mentions that the value of governance is in the actions, behaviors, and decisions made about data. According to Mazzarella, a large budget isn’t necessary. The need is to understand the challenges of data to build a conceptual model of how business works, understand the actual data, and then create solutions.

He explains that 80% of the job is human. It is about people, behavior, and relationships, and that starts with having conversations.

Speaking on what it takes to be a change agent, Mazzarella affirms that leaders have to have the soft skills to tell a story, have relationships, build trust, read a room and understand what is needed. This is key to overcoming the resistance to change.

Further, he talks about his approach to building a team. Mazzarella reveals that he is open to getting people from different perspectives but that they have to be smart problem solvers. They do not necessarily need a computer science background; they can be from operations, frontline employees, and the business side, he adds.

Mazzarella concludes by saying that he can also have people with humanities’ backgrounds because some of their skills apply to data governance, metadata management, and all the related disciplines.

[This content was originally published on cdomagazine.tech.]

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(US and Canada) Anthony Mazzarella, Director of Data Governance, Voya Financial, speaks with Michael C. Fillios, Founder & CEO, IT Ally, about his career in data management, data governance at Voya, and the need to be part of industry communities.

Mazzarella grew up around technology and computers. Technical knowledge and good soft skills allowed him to understand, visualize and articulate technology solutions. Hence, his technology profession happened naturally.

He started working in the financial services industry in analytics and eventually evolved to building a digital domain and moving to data governance. It was a great opportunity but also presented data government implementation challenges. Mazzarella describes his role as an enabler and a collaborator, pulling everything and everyone together and reducing barriers to entry for other parts of the organization.

Voya follows a federated approach, focusing a lot on supporting the data strategy. In its early cloud transition, the company focuses on metadata, the controls, and working with architecture to define the vision of having embedded governance and quality controls throughout the ecosystem.

Mazzarella maintains that while the organization is pro-regulation and puts customers first, it tries to protect their data.

Sharing his experience of being part of industry organizations like DAMA (Data Management Association) on a domestic and international level, he says that he wouldn’t trade that community experience for anything in the world. The organization plays an integral role in building bodies of knowledge by gathering data worldwide and sharing information, knowledge, and culture.

[This content was originally published on cdomagazine.tech.]

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(US and Canada) Jennifer Bachner, Director, Data Analytics and Policy Program, The Johns Hopkins University, speaks with Michael C. Fillios, Founder & CEO, IT Ally, about her career in data analytics and applying analytics for efficient law enforcement.

Bachner initially pursued her Ph.D. in political science to study public opinion on political behavior. She was exposed to analytics while using it to discern political behavior.

She points out that evidence-based policymaking is one of the most important uses of analytics. Over the last few years, government agencies have invested substantial resources in developing their analytic capacities, leading to improved government services and programs in various areas.

Accordingly, in 2014, Johns Hopkins launched a Master of Science in Government Analytics for professionals in the public and private sectors.

Bachner says that apart from good statistical analysis, analytics leaders need creativity and communication skills. She notes that a good analytics leader must communicate findings effectively.

According to her report on preventing crime with data and analytics, she says that police officers are using analyses correctly to forecast and prevent crime. However, data-driven approaches are not substitutes for the relationships and trust officers must build with citizens to create safe communities. They must also address privacy and security concerns as they develop and manage their data analytics capabilities.

Sharing her perspectives on the challenges of evolving government analytics, Bachner says that the Foundations for Evidence-based Policymaking Act of 2018 — also referred to as the Evidence Act — is one of the biggest change catalysts. It requires all government agencies to develop statistical evidence to inform policy-making and increase government data access.

One of the biggest challenges analytics leaders face is securing buy-in from organization leaders and employees who are skeptical about over-reliance on data. Another significant challenge she points out is resource investment.

She suggests addressing that challenge in three steps. First, leaders must demonstrate good stewardship with the resources given. Second, they must be specific and goal-oriented in their requests for resources and be clear about what tasks need to be completed. Finally, analytics leaders must retain qualified staff who can perform rigorous analysis and communicate findings clearly.

[This content was originally published on cdomagazine.tech.]

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(Europe) Lorraine Waters, Chief Data Officer at Solidatus, speaks with Michael C. Fillios, Founder and CEO, IT Ally LLC, about the C-suite interactions within technology organizations,  data security, characterization of modern CDOs, data commercialization, data analytics, and organizational challenges faced by CDOs and how to overcome them.

Waters starts the discussion by explaining the different C-suite interactions and how, despite existing as distinct roles, they are additional shoulders to the organizational wheel. She states that a Chief Data Officer is capable of supporting and servicing digital transformation and analytic roles. Whether it pertains to the CDO’s domain or other C-suite levels, they need to work in coherence. She adds that it is the CDO’s role to make data accessible to analytics and digital teams while prioritizing the security aspect of data.

Waters highlights the importance this role holds in strengthening the role of Chief Information Security Officer (CISO). Calling the latter a technical role, she states the organization needs to incorporate specialized defenses. A good understanding of data flow through the organization — a data blueprint provided by the CDO — helps the CISO learn the whereabouts of data and if required control measures are maintained. The two roles are interconnected, she states, and the CDO is key to the CISO’s success.

Waters further points out that having a business mindset, product management skills, and data privacy and ethics management are some of the characteristic requirements for a CDO. Waters also firmly believes that to be a skilled and successful CDO, a robust commitment to diversity, equity, and inclusion is necessary. This not only develops data culture and a talent pool around data management but also incorporates different perspectives to promote better civil data protection among other subjects, she states.

In the context of internal data commercialization, Waters says that data management has been a tax on the business. An effective data management capability and a CDO to market that capability and portray the benefits of good data management are also necessities. She considers data blueprint creation to be a critical tool that helps the CDO process data categorization and cataloging and learn data lineage.

Concerning external data commercialization, she states that there have been numerous attempts to commercialize and make data available across organizations. Some of them have been successful but many have failed due to an organization’s reluctance to share data, often because of data sensitivity or poor data quality. In addition, customers do not want suppliers to increase sales based on their data, and they are becoming increasingly aware of their rights regarding data usage. This, says Waters, has narrowed the opportunities for data commercialization. Based on the developing standards around ESG data, she urges industries to focus collectively on data standardization.

Speaking of SMEs, Waters states that small organizations starting on a data journey may research leading industry bodies like EDM Council, DCAM, etc., for learning data strategies. She affirms that understanding data is easy once the basic foundational knowledge is acquired.

She urges companies to understand business strategies to reap outcomes, and emphasizes the importance of delivering business benefits for consumers and implementing long-term strategies. This is where a practical and commercial-minded CDO is beneficial, she adds.

Regarding the many challenges faced by CDOs concerning data management, Waters notes how certain banks she previously worked with were subject to enforcement action by regulators. She maintains that the focus should have been on preventive controls rather than detected weaknesses. She urges CDOs to create data lineage first, understand the data flow to control weaknesses, and fix them gradually.

She says that financial regulators, as the largest data collectors, have made strides by acquiring all necessary data and disclosures from financial services companies. The regulators and CDOs have come to shake hands on prioritizing proactive, preventive, and sustainable control overriding the hamster wheel of detection and remedy, Waters concludes.

[This content was originally published on cdomagazine.tech.]

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(US and Canada) Kelly TeDesco, Senior Director of Data Science, The Gorilla Glue Company, speaks with Michael C. Fillios, Founder and CEO of IT Ally, about talent retention in IT, an approach to data literacy, and adoption of technology in smaller organizations.

How to retain talent given the shortage of talent in the market today? TeDesco says that data scientists want to continue to learn and grow beyond the title or money. It is really about the work they do. TeDesco tries to reward her team members with good work by giving them projects that develop them and make them feel like supported data scientists.

Sharing a couple of specifics, she says that data scientists want to learn the most modern technology available and also have the flexibility of working in either a hybrid or remote working setup.

She then discusses the ideal approach to establishing data literacy within a company. She stresses that data literacy grows over time and is necessary to have the capabilities and to enable data scientists.

TeDesco explains that the change management required to instill data literacy in an organization can take time and constant repeated efforts. It also helps to share some of the details and build trust about the outcome being delivered and the processes.

Highlighting ways to adopt an approach, she says that using consistent types of visual information makes it easier for business counterparts to understand things. The next step is to have open dialogue, encourage questions, and have more than one way to explain concepts.

To describe her role in simple terms, TeDesco says that it changes depending on the task at hand. In her previous assignment, her role was to understand data and help the company figure out the right price and the right products on the shelf. At Gorilla Glue, her role is to build out the data science function.

Sharing tips for small businesses regarding ways to embrace data analytics, she says that it is important to focus on the transition to ensure adoption. Successful projects are ones where the transition happened and allowed the company to gain adoption.

[This content was originally published on cdomagazine.tech.]

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(US and Canada) Kelly Tedesco, Senior Director of Data Science, The Gorilla Glue Company, talks with Michael C. Fillios, Founder and CEO of IT Ally, about her passion for analytics.

Tedesco is an undergraduate and graduate in Decision Sciences and Quantitative Analysis, both of which are the application of statistics to operations and business. She started her career with Victoria’s Secret, building statistical models to determine who received catalogs. After about four years, Tedesco moved to Dunnhumby, USA, which is now 8451, the data science arm of Kroger. She spent over 13 years working with Kroger data and held various roles there. While at Kroger, she was in the merchandising section answering business questions about Kroger customers, usually regarding loyalty price and promotion response, and in-store behavior. Tedesco spent about three years building new capabilities around the Kroger pharmacy data, which was exciting because it was a new industry for her and allowed her to be creative with new types of analysis.

Next, she developed a measurement science center of excellence, an intense dive for her in statistical capability and developing software as a service. While those two roles were quite different from each other, they both provided opportunities for Tedesco to develop something new … something that would be used throughout the business for a time to come. And that’s what appealed to her about Gorilla Glue.

Tedesco joined Gorilla Glue as the first data scientist and developed the function. She looks forward to finding the value the company gets from the data and building something that will become integral to the business.

Tedesco deems herself fortunate to have found her passion for analytics during her undergraduate days at Miami University in Oxford, Ohio. Although decision science was not a typical degree at the time, Miami University offered it. Because Tedesco preferred math and numbers, she decided to give decision science a try. She also has a double major in finance.

Data science is the most fun, she says, with tasks varying from problem solving to coding visualizations, developing insights, and telling stories — all integral to businesses gleaning value from its data. Science doesn’t necessarily tell people the answer, Tedesco notes. But it provides a lot of evidence and decisions and, in most cases, it’s difficult to argue with the data.

[This content was originally published on cdomagazine.tech.]

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(US and Canada) Ali Khan, Chief Data Officer at Experian Consumer Services, speaks with Michael C. Fillios, Founder and CEO of IT Ally, about data governance in an SMB, precautions to be considered, data security, data quality, and Scholastic’s cloud journey.

Regarding data governance, Khan thinks that it is just a question of scale. The data-related activities are similar, regardless of size. It starts with cataloging data, which answers the whereabouts of data. Then comes the access factor, which decides who has access to data and is implementing it. The third part is data enablement, which he believes is the pot of gold at the end of the rainbow. After understanding the data through cataloging and having the right people accessing it, data enablement means the data is used for benefit.

He believes that the process holds for Experian as well as for an SMB. Khan further suggests that SMBs should think before adopting data governance tools as they go through a cycle of bundling and unbundling within the data management ecosystem.

Khan states that companies can buy data catalogs and other open-source tools while being cautious about adding more features and raising expenses. He says that with small and medium-sized businesses, it is crucial to understand the type of adoption they want without spending more than what is needed. With additional tools, an SMB would also incur the operational cost of a heavy system without having the right kind of adoption needed.

He highlights the security aspect of data by affirming Experian as a data security company. It has a breach detection and advisory division, which advises the world’s largest security-conscious companies on data breaches. With services like dark web monitoring, Khan ensures that Experian is uncompromising when it comes to data security.

Next, addressing data quality, he describes it as an ongoing challenge and something that is never done right. Khan prefers a realistic approach when it comes to data quality by setting data boundaries and expectations. Understanding the available data and building its value while keeping in mind its sensitivity and assigning ownership, is the key to achieving data quality, he says.

Regarding Scholastic, Khan states that cloud providers now have strengthened data security with data governance.That, according to Khan, was the first challenge, and the breakthrough was in realizing that security posture could be improved by doing cloud right. He mentions that educational psychologists there were skeptical of machine learning due to the lack of well-trained models in the past. However, acceptance came with the understanding of the level of outcome that could be generated through machine learning.

On an ending note, Khan advises data enthusiasts and future data engineers to be curious and tenacious. When he asks his teammates about what inspired their interest in data and what excites them, the answer is often “Curiosity.”

[This content was originally published on cdomagazine.tech.]