Remove Dashboards Remove Data Quality Remove Experimentation
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6 DataOps Best Practices to Increase Your Data Analytics Output AND Your Data Quality

Octopai

DataOps is an approach to best practices for data management that increases the quantity of data analytics products a data team can develop and deploy in a given time while drastically improving the level of data quality. Products should be ready-to-consume, easily accessible and responsive to the consumers’ needs.

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The top 15 big data and data analytics certifications

CIO Business Intelligence

Individuals with the certificate understand how to clean and organize data for analysis, and complete analysis and calculations using spreadsheets, SQL, and R. They can visualize and present data findings in dashboards, presentations, and commonly used visualization platforms.

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What is DataOps? Principles and Benefits

Octopai

Today, your business users have the same perspective on data analytics. Your dashboards, charts, visualizations… they’re all products. . A successful data analytics team is one that can increase the quantity of data analytics products they develop in a given time while ensuring (and ideally, improving) the level of data quality.

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What you need to know about product management for AI

O'Reilly on Data

Because it’s so different from traditional software development, where the risks are more or less well-known and predictable, AI rewards people and companies that are willing to take intelligent risks, and that have (or can develop) an experimental culture.

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Advanced Data Discovery and Augmented Analytics: Simple, Sophisticated Tools for Business Users

Smarten

The tools exist today for augmented analytics, augmented data discovery, self-serve data preparation and other features and modules that provide sophisticated functionality and algorithms in an easy-to-use dashboard and environment that is designed to support business users, as well as data scientists and IT staff.

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Knowledge

Occam's Razor

Slay The Analytics Data Quality Dragon & Win Your HiPPO's Love! Web Data Quality: A 6 Step Process To Evolve Your Mental Model. The Ultimate Web Analytics Data Reconciliation Checklist. The "Action Dashboard" (An Alternative To Crappy Dashboards). Who Owns Web Analytics?

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The DataOps Vendor Landscape, 2021

DataKitchen

RightData – A self-service suite of applications that help you achieve Data Quality Assurance, Data Integrity Audit and Continuous Data Quality Control with automated validation and reconciliation capabilities. QuerySurge – Continuously detect data issues in your delivery pipelines. Data breaks.

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