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Data, Analytics and AI
Developing Autonomous Data Competencies for Real Value & Analytics-Readiness
The concept of data integration can mean different things to different people, but for this purpose, it means “joining, combining or linking data from more than one source.” Generally, the data needs to have shared characteristics, so that it should be “about people or businesses,” and it can also be “integrated over time to create a longitudinal dataset.” But to really get the most out of the data, it also needs to interact with other datasets. For instance, “educational outcomes are not just affected by what’s happening in the classroom, they’re also affected by other things like health and family …
Data, Analytics and AI
Speaker Spotlight Q&A with Sarah Truckle, Director of Program and Strategic Operations at the State of Vermont's Agency of Human Services
She has graduate degrees in both law and environmental policy from Vermont Law School. In her role within the Secretary’s Office, she leads the agency’s integration and care coordination through complex case management, directing the systems-level coordination of agency resources and community partner services. Additionally, her work integrates the Agency’s strategic operations supporting programmatic and fiscal alignment. Outside of work Sarah enjoys baking cakes and pastries, reading fiction, and walking through Hubbard Park with her two sons.
Data, Analytics and AI
Democratizing Analytics in the Public Sector
Transforming Data into Breakthroughs for the Public Sector The global pandemic that we are still living through has changed much of the way society operates, though even before the onset of COVID-19, most people accepted that modern societies were data-driven. Data is essentially the fuel that powers our societies, and it is so pervasive that the latest DOMO ‘Data Never Sleeps 9.0’ report found that the total amount of global data consumed in 2021 was 79 zettabytes (1021), projected to grow to 180 zettabytes by 2025. These numbers are staggering in their magnitude, but to the average citizen they are …
Data, Analytics and AI
Data Management & Analytics Roadshow 2022 Highlights
This year's Data Management and Analytics Roadshow focused on exploring emerging techniques for data visualisation such as Data Sharing and Artificial Intelligence, as we shared real-world case studies and engage in thought-provoking roundtables.
Data, Analytics and AI
Accelerating Data and Automation Transformation in the Public Service
When it comes to data verification, there are essential “three possible ways of proving who I say I am: through something I have, like a document or a card; through something that I know, like a name or a password; or through who I am, like fingerprints or facial recognition.” Biometrics is related to the third of these options, and there are a number of reasons why biometrics is the preferred option. Without biometrics, the verification of identity can be time-consuming and often has to be conducted “in service centres in-person.” On top of that, “the transaction is cumbersome both …
Data, Analytics and AI
Data Visualisation and Dashboards Techniques
As an example, many people will know the colours of Google even if they don’t see the word spelled out, and they will know the font of Disney even if it is used to write something else. A lot of these kinds of brands are ingrained in our minds because they use all four elements and because “everything that we consume visually makes use of those well-known attributes within our brains.” In an organisation like the Inland Revenue Department there are four factors that have been included in the style guide, “though more elements can be added in there.” These …
Data, Analytics and AI
Spotlight Interview: Data Management & Analytics Roadshow 2022
The general trend we are seeing in the industry is toward the integration of multiple different concepts and technologies to create an accurate picture of the entirety of an organisation's data landscape. Two prominent examples are the data fabric and data mesh architectures. In both cases, there is an emphasis on automation around metadata management, where metadata is viewed as “fuel” for AI-driven decision-making around automated data ops. As Data Fabric matures, we see that metadata management will require big updates on the conceptual level. To properly employ AI to drive data management tasks, metadata management solutions will have to …
Data, Analytics and AI
Government Innovator Spotlight Q&A: Ed Kelly, CDO, State of Texas
As CDO for the State of Texas my role is multi-faceted. I have the great opportunity to work with almost every state agency and institution of higher education helping them to develop their data management programs. The office of the Chief Data Office (OCDO) serves as the chief evangelist for data best practices, as well as data broker, facilitator, trainer, and collaborator. I have worked in Texas state government for 14 years as a CIO, CAO and now a CDO for 6 years. When the opportunity came up to develop and manage a statewide program, I was very interested. Guess …
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