Tue.Nov 22, 2022

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10 Most Common Data Quality Issues and How to Fix Them

KDnuggets

Ensuring data quality guarantees more data-informed decisions. Hence, this article highlights the common data quality issues and ways to overcome them.

Data 108
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A (Stream Processing Use Case) Recipe for Thankfulness

Confluent

Our Stream Processing tutorials help you tackle real-life use cases with Apache Kafka and ksqlDB. Check out our newest Thanksgiving-themed use case: survey response analysis!

Process 57
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Will Poor-Quality Data Undermine your Business?

KDnuggets

Leverage precise data to discover business opportunities, make strategic decisions, and increase ROI with a powerful data quality platform.

Data 99
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How Data and Finance Teams Can Be Friends (And Stop Being Frenemies)

Monte Carlo

Recently I wrote an article about data silos that form across the organization, often due to lack of alignment with partners. This alignment can be difficult to come by, but is crucial to a data leader’s success. With the range of internal customers to support, it can be tempting for data teams to inhabit the principles of an assembly line or even a fry cook at McDonalds.

Finance 52
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From Developer Experience to Product Experience: How a Shared Focus Fuels Product Success

Speaker: Anne Steiner and David Laribee

As a concept, Developer Experience (DX) has gained significant attention in the tech industry. It emphasizes engineers’ efficiency and satisfaction during the product development process. As product managers, we need to understand how a good DX can contribute not only to the well-being of our development teams but also to the broader objectives of product success and customer satisfaction.

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Best Practices for Customer-Facing Analytics Dashboards | Propel Data Analytics Blog

Propel Data

Learn the best practices when designing your customer-facing analytics dashboards, as well as some common antipattern practices to avoid.

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How SeatGeek Reduced Data Incidents to Zero with Data Observability

Monte Carlo

Data downtime, unknown unknowns, and the specter of schema changes loom large for data teams of all stripes, and the team at SeatGeek was no exception. As the only mobile ticketing marketplace built for fan experience, SeatGeek made its name on efficient customer experiences. So, when SeatGeek’s data leaders realized they were losing too much time root-causing data issues in their BI reports, they began looking for tools to help them discover their data problems faster.

Data 52
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How to move data from spreadsheets into your data warehouse

dbt Developer Hub

Once your data warehouse is built out, the vast majority of your data will have come from other SaaS tools, internal databases, or customer data platforms (CDPs). But there’s another unsung hero of the analytics engineering toolkit: the humble spreadsheet. Spreadsheets are the Swiss army knife of data processing. They can add extra context to otherwise inscrutable application identifiers, be the only source of truth for bespoke processes from other divisions of the business, or act as the transl