Secrets Of Data Analytics Leaders ציבורי
[search 0]
עוד

Download the App!

show episodes
 
Discover the strategies that convert data into insights and action. Acclaimed data analytics leaders will unearth the secrets of their success in each episode. Subscribe below to stay abreast of the best practices, trends, and technologies driving our fast-paced industry! For transcript articles of the podcasts visit https://www.eckerson.com/podcasts/secrets-of-data-analytics-leaders
 
Loading …
show series
 
In this episode, we explore an area of data analytics that everyone knows they need to improve but no one knows how to do it. That is data literacy. Data literacy ensures that business people have the skills to accurately interpret data represented in charts, tables, and dashboards, as well as the knowledge to use those tools to gather and analyze …
 
Every December, Eckerson Group fulfills its industry obligation to summon its collective knowledge and insights about data and analytics and speculate about what might happen in the coming year. The diversity of predictions from our research analysts and consultants exemplifies the breadth of their research and consulting experiences and the depth …
 
The COVID shock forces enterprises in every market to accelerate and reshape their data analytics strategies. This trend is likely to continue. “Data Elite” enterprises survived this year through a mix of agility, efficiency, and intelligence. They met these requirements of survival as they accelerated their digital transformations, adopted cloud d…
 
Continuous Intelligence (CI) integrates historical and real-time analytics to automatically monitor and update various types of systems, including supply chains, telecommunications networks and e-commerce sites. CI encompasses data ingestion, transformation and analytics, as well as operational “triggers” that recommend or initiate specific real-ti…
 
This blog compares Predictive vs Prognostic analytics and gives a quick view into systems dynamics and causal modeling. If it sparks your interest, watch for an upcoming series of articles connecting the practices of systems thinking, causal analysis, and analytics.Originally published at: https://www.eckerson.com/articles/looking-at-the-future-thr…
 
This blog is about Continuous Intelligence (CI) and how it integrates historical and real-time analytics to operate, monitor and tune systems of all types. Our next blogs will explore architectural approaches to CI, and how to navigate the trade offs it introduces to your organization.Originally published at: https://www.eckerson.com/articles/conti…
 
This blog is about Graphics Processing Units (GPU) and how much of the focus and industry growth in the use of GPUs has come from their suitability for machine learning, especially neural networks, more commonly known as deep learning. Originally published at: https://www.eckerson.com/articles/gpu-databases-getting-more-value-from-your-machine-lear…
 
This blog is about the challenge of data sprawl and how the combination of AI-based entity matching, schema matching, and enhanced knowledge graphing is moving us ever closer to the vision of self-driving data.Originally published at: https://www.eckerson.com/articles/using-data-knowledge-to-conquer-data-sprawl…
 
This EG blog is about data modernization steps and guiding principles that can help maintain balance within schools, stores, and other face to face businesses affected by COVID-19. Originally published at: https://www.eckerson.com/articles/covid-19-and-higher-education-a-case-study-in-data-modernization…
 
This is an audio blog on BI on the Cloud Data Lake and how to improve the productivity of data engineers. We'll dive deeper into the question; what’s the best measure of success for data pipeline efficiency? This is part 2 of a two part blog. Originally published at: https://www.eckerson.com/articles/business-intelligence-on-the-cloud-data-lake-par…
 
This audio blog is about business intelligence on the cloud data lake and why it arose and how to architect for it.This is Part 1 of a two part blog series. Originally published at: https://www.eckerson.com/articles/business-intelligence-on-the-cloud-data-lake-part-1-why-it-arose-and-how-to-architect-for-it…
 
This audio blog is about the data lakehouse and how it is the latest incantation from a handful of data lake providers to usurp the rapidly changing cloud data warehousing market. It is one of three blogs featured in the data lakehouse series.Originally published at: https://www.eckerson.com/articles/all-hail-the-data-lakehouse-if-built-on-a-modern…
 
This is an audio blog about the perplexities of the Data Lakehouse and if it is, indeed, the "paradigm of the decade".To hear more of Eckerson Group perspectives on the data lakehouse be sure to check out the blogs from colleagues, Wayne Eckerson and Kevin Petrie, and the recording of our recent Shop Talk discussion.Originally published at: https:/…
 
This audio blog discusses the Data Lakehouse, a marketing concept that evokes clean PowerPoint imagery, and why and how the New Cloud Data Lake will play a very real role in modern enterprise environments.Originally published at: https://www.eckerson.com/articles/data-lakehouses-hold-water-thanks-to-the-cloud-data-lake…
 
This audio blog discusses cloud adoption and how data teams will migrate an increasing portion of their on-premises operational and analytics workloads to the cloud. They can best meet budget and project requirements by using data streaming technologies such as change data capture (CDC), which replicates real-time updates between data source and ta…
 
This audio blog is about how the CHOP’s data and analytics (DnA) team uses near real-time data and information to decide how to marshal its resources to contain the pandemic. The culmination of all of this work has been an enterprise COVID-19 dashboard that is distributed to enterprise leadership daily.Originally published at:https://www.eckerson.c…
 
This audio blog is about the emerging concept of the data mesh and how enterprises are working tirelessly to centralize diverse, ever-multiplying datasets by transforming mountains of data they don’t understand, into information that analysts do understand.Originally published at: https://www.eckerson.com/articles/the-data-mesh-re-thinking-data-int…
 
As of this writing, billions of consumers live in quarantine. They buy what they need online, comforting themselves with food, TV, and toilet paper. Nobody is splurging at the mall.To say the least, it is an interesting time to analyze discretionary consumer behavior. As Director of the Voice of Consumer Analytics at Adidas, Tiankai helps measure a…
 
This audio blog focuses on data storytelling and how it uses numbers, narrative, and visuals to communicate insights that would otherwise be hard to absorb. Originally published at: https://www.eckerson.com/articles/data-storytelling-part-i-telling-it-like-it-is-and-was-and-will-beעל ידי Eckerson Group
 
This audio blog focuses on increase usage of NLP to navigate different formats, languages, terminologies, and biases and how this technology will help analyze the fast-growing body of research on COVID-19.Originally published at:https://www.eckerson.com/articles/how-covid-19-will-drive-adoption-of-natural-language-processing…
 
Chief data officers (CDOs) first appeared in enterprise organizations after the Sarbanes Oxley Act became law in the United States in 2002 to improve corporate governance controls. CDOs started with a trickle, but have since become a flood, now populating more than two-thirds of large enterprises, according to a recent survey by NewVantage Partners…
 
A chief data officer not only defines a data strategy to meet current needs but also evolves the strategy to ensure that the organization derives value far into the future.Originally published at https://www.eckerson.com/articles/seven-core-responsibilities-of-a-chief-data-officer-cdoעל ידי Eckerson Group
 
Data leaders who launch self-service analytics programs without knowing their business users risk unleashing chaos. Data leaders need to canvas the organization and understand who produces what information for whom and where.Originally published at https://www.eckerson.com/articles/succeeding-with-self-service-analytics-know-thy-customer…
 
Master Data Management is no shiny object. But like many traditional IT practices, MDM is being severely tested – and rendered all the more strategic – by digitalization and rising data volumes.Originally published at https://www.eckerson.com/articles/five-master-data-management-best-practices-for-enterprises…
 
The rise of machine learning has placed a premium on finding new sources of data to fuel predictive models. But acquiring external data is often expensive and many data sets are rife with errors and difficult to combine with internal data. But that’s going to change in 2020. To help us understand the scale, scope, and dimensions of emerging data ma…
 
Data quality and leadership trust levels may not seem connected, but they’re inextricably linked. Here’s why ...Originally published at https://www.eckerson.com/articles/using-data-quality-to-build-trust-in-the-business-leadersעל ידי Eckerson Group
 
Data is critical for learning about the needs of the market, product bugs and issues, competitive solutions, and many other things. As such, analytics plays an important role in the innovation process.Originally published at https://www.eckerson.com/articles/how-can-analytics-support-business-innovation…
 
All organizations need to go down a similar path of data maturity. While you can skip steps in technology, you can’t skip steps in business data maturity.Originally published at https://www.eckerson.com/articles/evolutionary-not-revolutionary-invest-less-in-new-tech-and-more-in-your-data-valuesעל ידי Eckerson Group
 
In this episode, Wayne Eckerson and Matthew Schwartz discuss non-traditional uses of business intelligence tools. Although BI tools have been around for almost three decades, most companies just scratch the surface of what’s possible to do with those tools. Using web layers and APIs, a company can use their imagination to customize and leverage the…
 
One of the hardest parts of running a data analytics program inside a large organization is governing data and reports. It’s simply too easy for the definition of core data elements and metrics to get out of sync and reports to contain conflicting information.Angie Davis has straddled both the business and IT worlds for more than 20 years. She serv…
 
This audio blog focuses on the importance of establishing a strong relationship between business and technical teams and describes various business engagement models that sit at the heart of all successful data analytics programs.על ידי Eckerson Group
 
Companies that excel at advanced analytics and data science maximize the value of their data. They unearth hidden opportunities and become innovators in the industry. Although each organization has different goals, the underlying processes and tools to become successful at analytics remain somewhat the same. In this episode, Alan Jacobson explains …
 
With the growing popularity of machine learning and artificial intelligence, creating a data science program is a key initiative at most companies today. However, it’s not always clear to executives how they can deliver a return on investments in data science. To explain this, we invited an expert who has spent most of his career in the data scienc…
 
How do you organize a data analytics program to maximize value for the organization? Although there is no right or wrong way to do this, several patterns emerge when you examine successful organizations.Originally published at https://www.eckerson.com/articles/organizing-for-success-part-ii-how-to-organize-a-data-analytics-program…
 
The goal of self-service analytics is to empower business people to build their own reports, dashboards, and predictive models. If that happens, does your company still need a corporate business intelligence team?Originally published at https://www.eckerson.com/articles/organizing-success-part-1-organize-bi-team…
 
Before a company hires data science talent, they should understand the role and types of data scientists. Failing to differentiate between research, applied, and citizen data scientist can result in appointing the wrong people on crucial projects. To continue our previous episode's discussion, we invited Alex Vayner for a second time to get an answ…
 
Data science has made immense progress, but companies are still stuck with the question: how do you use data science to deliver real value to the business? They hire dozens of data scientists and invest in state-of-the-art technology, but only a few have delivered ROI and business impact. In this episode, Wayne Eckerson and Alex Vayner discuss what…
 
IoT has created a tidal wave that data savvy organizations can turn into profitable business solutions. Most IoT data comes from sensors, which are now attached to almost every device imaginable, from factory floor machines and agricultural fields to your cell phone and toothbrush. But IoT is forcing companies to rethink their data architectures to…
 
Just-in-time design is the practice of designing working software in small increments that support a business-defined need or story. Just-in-time design, as well as just-in-time testing, is an integral part of the agile software methodology. In fact, you can’t really do agile without just-in-time design. To help us understand the nuances of just-in…
 
Last month, I attended Domo’s annual user conference for the first time. I came a skeptic, but left a believer. Domo has invested large sums of money to create a comprehensive data and analytics platform that scales to run small and medium-size businesses, and possibly large ones. Most importantly, it has a cadre of highly satisfied brand-name cust…
 
Processing continuous data streams is becoming increasingly important. However, traditional analytics architectures were often not built for real-time scenarios. This article will illustrate challenges and discuss how streaming-first approaches can change the way we think about analytics architectures.Originally published at: https://www.eckerson.c…
 
This second article in a series on modern data architectures. It focuses on what drives customers to want a modern data architecture (i.e., fear and opportunity) in the first place. It then lists ten requirements that customers desire for a modern data architecture, ranging from “cloud-first” and “streaming-first” to “best of breed” and “predictabl…
 
Data virtualization has been around for decades and has always been controversial. In the 1990s, it was called virtual data warehousing or VDW-- or as some skeptics liked to say, "voodoo and witchcraft”. It’s also been known as query federation and more recently, data services. The idea is that business users don't need to know the location of the …
 
Why is Data Quality still an issue after all these years? To get an answer to the prevalent question, Wayne Eckerson and Jason Beard engage in a dynamic exchange of questions which lead us to the root cause of data quality and data governance problems. Using examples from his past projects, Jason shows the value of business process mapping and how …
 
Loading …

מדריך עזר מהיר

זכויות יוצרים 2021 | מפת אתר | מדיניות פרטיות | תנאי השירות
Google login Twitter login Classic login