Data Analytics | Chuck Muizers

Data

COVID, inflation, broken supply chains, and not-so-distant war make this a turbulent time for the modern consumer. During times like these, families tend to their nests, which leads to lots of home-improvement projects…which means lots of painting.

Today we explore the case study of a Fortune 500 producer of the paints and stains that coat many households, consumer products, and even mechanical vehicles. While business expands, this company needs to carefully align the records that track hundreds of suppliers, thousands of storefronts, and millions of customers.

Business expansion and complex supply chains make it particularly important—and challenging—for enterprises such as this paint producer, which we’ll call Bright Colors, to accurately describe the entities that make up their business. They need to be governed, validated data to describe entities such as their products, locations, and customers. Master data management, also known as MDM, streamlines operations and assists data governance by reconciling disparate data records into golden records and ideally a single source of truth.

We’re excited to share our conversation with an industry expert that helps Bright Colors and other Fortune 2000 enterprises navigate turbulent times with effective strategies for MDM and data governance.

Dave Wilkinson is chief technology officer with D3Clarity, a global strategy and implementation services firm that seeks to ensure digital certainty, security, and trust. D3Clarity is a partner of Semarchy, whose Intelligent Data Hub software helps enterprises govern and manage master data, reference data, data quality, enrichment, and workflows. Semarchy sponsored this podcast.

Dave Wilkinson: Enterprise Data Governance and MDM Case Study

Designed and implemented well, automated workflows can make the modern business just a little less chaotic and complex. This blog explores the opportunity for automated workflows to help cross-functional teams collaborate and standardize organizational master data.
Published at:
https://www.eckerson.com/articles/master-data-management-and-operational-workflows-two-modern-use-cases

Master Data Management and Operational Workflows: Two Modern Use Cases

Join us this week on the New Zealand Initiative podcast! Our host, Dr Eric Crampton chats with Professor Rhema Vaithianathan from Auckland University of Technology. Rhema gives us a peek into her pioneering work on data-tools, designed with a human touch to better serve communities.

In this fascinating chat, they delve into Rhema's trailblazing project, the Allegheny Family Screening Tool. This unique decision-aid tool is a global first, introduced in 2016 to support child welfare hotline screening. The duo also touch on the equally impressive Allegheny Housing Assessment tool, another innovative machine-learning tool used since 2020 for prioritising housing within the homelessness system.

Rhema reveals the power of predictive risk modelling in the US child protection system, where her team used administrative data to help improve outcomes for children. Listen to how this model uses past case data to guide operators in their decisions regarding potential abuse cases.

In the US, this approach worked to substantially reduce child hospitalisation. It could be done in New Zealand as well. In fact, the work started here. But New Zealand’s politics and public service has a very difficult time with new approaches. American localism means that one innovative county can try it out, and demonstrate the benefits to others.

All this and more in our enlightening podcast. Stay tuned for Part Two, where the conversation on AI and predictive models in child protection systems, and on encouraging public sector innovation more broadly, continues!

Podcast: Data analytics for social impact (part one)

ข้อมูลของเรา เวลามีขนาดไม่เยอะ ใช้เครื่องมือธรรมดาอย่าง spreadsheet ก็น่าจะเพียงพอแล้ว แต่เวลาข้อมูลมีขนาดใหญ่ มันก็จะไม่ง่ายอย่างนั้น วันนี้คุณไอซ์ วรุฒ กฤษรุ่งเรือง Senior Data Engineer จากบริษัท Data Wow จะมาเล่าให้ฟัง ตั้งแต่ต้นทาง ไปจนถึงปลายทาง Data Pipeline ทำอย่างไร ยากไหม ติดตามได้ในตอนนี้
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คำถาม
1. Data Pipeline คืออะไร แล้วมันมีประโยชน์อย่างไรครับ
2. อะไรเป็นองค์ประกอบของ Data Pipeline แล้วแต่ละส่วนมันเชื่อมโยงกันอย่างไร
3. อะไรเป็นความท้าทายเวลาเราต้องสร้าง หรือ Maintain Data Pipeline ครับ
4. ระหว่าง Batch Processing กับ Real-Time/ Streaming Data Pipeline เราเลือกใช้อย่างไร
5. คำว่า Data Pipeline คือการเอาข้อมูลมายัดใส่พวกตระกูล BigQuery หรือ RedShift หรือเปล่า
6. มีเคสที่ Data Pipeline มีบทบาทสำคัญกับธุรกิจมาเล่าให้ฟังไหม
7. อะไรเป็น Technology ที่น่าสนใจและต้องจับตามองสำหรับการทำ Data Pipeline
8. ถ้าวันนี้เราจัดการกับข้อมูลจำนวนหนึ่ง แล้วในอนาคตข้อมูลเยอะขึ้นมากๆ เราจะจัดการหรือเตรียมความพร้อมกับ Data Pipeline ได้อย่างไร
9. เราสามารถทดสอบได้ไหม ว่า Data Pipeline เราทำงานได้อย่างถูกต้อง
10. Data Pipeline มีผลกับการทำ Machine Learning หรือ Data Analytics ไหม
11. มีข้อแนะนำให้คนฟัง เวลาที่คิดจะสร้าง Data Pipeline ควรจะต้องคิดถึงเรื่องอะไรบ้างไหม

Data Pipeline ศิลปะของการจัดการข้อมูล กับคุณวรุฒ กฤษรุ่งเรือง | Tech Monday EP.139

Chief Data Officers are expanding data sharing to drive productivity, innovation, and better decisions. Data marketplaces simplify access by connecting users to ready-to-use, high-value data through a centralized, self-service platform.
Published at:
https://www.eckerson.com/articles/how-data-product-marketplaces-enable-seamless-data-consumption-and-generate-value

How Data Product Marketplaces Enable Seamless Data Consumption and Generate Value - Audio Blog

Only You - gin$eng

In this episode, Wayne Eckerson and Jeff Magnusson discuss the data architecture Stitch Fix created to support its data science workloads, as well as the need to balance man and machine and art and science.

Magnusson is the vice president of data platform at Stitch Fix. He leads a team responsible for building the data platform that supports the company's team of 80+ data scientists, as well as other business users. That platform is designed to facilitate self-service among data scientists and promote velocity and innovation that differentiate Stitch Fix in the marketplace. Before Stitch Fix, Magnusson managed the data platform architecture team at Netflix where he helped design and open source many of the components of the Hadoop-based infrastructure and big data platform.

Jeff Magnusson: Architecting for Data Science And Blending Man And Machine

In April 2019, the Harvard Business School Digital Initiative brought together academics and practitioners for an idea exchange around technology in a multidisciplinary world. This Future Assembly flash talk features Ayelet Israeli from Harvard Business School discussing "The added value of data analytics: evidence from online retailers." To learn more, check out digital.hbs.edu.

Transcript: https://hbs.me/3bQ28EG

Ayelet Israeli on the added value of data analytics | Future Assembly 2019

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 served as a business analyst in several organizations before switching to the information technology side of the business where she ran analytics teams, first at JD Irving for six years and more recently at Brookfield Renewable where she is an IT director. Angie has a degree in mathematics and electrical engineering from Dalhousie University in Halifax, Nova Scotia.

Angie Davis: Overcoming Report and Data Governance Obstacles

Listen to data and analytics leaders share the secrets of their success. Wayne Eckerson, long-time global thought leader interviews guests who run data and analytics programs at Fortune 2000 organizations around the world. Tune in to stay abreast of the latest technologies, techniques, and trends in our fast-paced industry.

Dave Wilkinson: Enterprise Data Governance and MDM Case Study

Secrets of Data & Analytics Leaders