self‑service analytics

Baidu Geek Talk

Apr 10, 2024 · Big Data

TDA: A One‑Stop Self‑Service BI Platform – Architecture, Challenges, and Solutions

The article presents Turing Data Analysis (TDA), a self‑service BI platform that replaces fragile traditional pipelines with a unified DWD‑based data model, drag‑and‑drop analytics, multi‑engine query optimization and caching, delivering sub‑10‑second queries on billions of rows, fine‑grained permissions, and rapid dashboard creation, while reporting significant usage growth and outlining AI‑driven future enhancements.

BIBig DataMPP

0 likes · 15 min read

TDA: A One‑Stop Self‑Service BI Platform – Architecture, Challenges, and Solutions

DataFunSummit

Jan 31, 2024 · Big Data

iQIYI Magic Mirror: Evolution of a Big Data Analysis Platform

iQIYI's Magic Mirror platform, evolving from 1.0 to 3.0, addresses the growing data analysis demands of the internet industry by empowering self‑service analytics, introducing multi‑stage architectures, advanced computation engines, customizable SQL, and visual dashboards, thereby improving efficiency, scalability, and data security for business users.

Big DataSQLdata-platform

0 likes · 18 min read

iQIYI Magic Mirror: Evolution of a Big Data Analysis Platform

DataFunSummit

Jan 4, 2024 · Big Data

YY Live Business Metric Governance Practice

This presentation details YY Live’s data product team’s end‑to‑end business metric governance practice, covering problem background, analysis, governance objectives, multi‑team collaboration, implementation steps, achieved efficiencies, and future directions leveraging large language models.

Big DataLLMMetric Management

0 likes · 16 min read

YY Live Business Metric Governance Practice

Zhuanzhuan Tech

Dec 27, 2023 · Big Data

Implementing Self-Service OLAP Analytics with Quick BI and StarRocks: Architecture, Optimizations, and Lessons Learned

This article presents a comprehensive case study of building a self‑service OLAP analytics platform at ZhaiZhai using Quick BI and StarRocks, covering background motivations, technical architecture, implementation details, performance‑optimizing case studies, and the resulting business impact.

Big DataData WarehouseOLAP

0 likes · 16 min read

Implementing Self-Service OLAP Analytics with Quick BI and StarRocks: Architecture, Optimizations, and Lessons Learned

Architecture Digest

Mar 22, 2023 · Big Data

Performance Platform: Accelerating Data Production and Consumption

This article details how the Performance Platform at Baidu speeds up data production and consumption across the company's R&D pipelines by introducing five optimization paths, 18 concrete methods, service tiering, compliance measures, and self‑service analytics for both real‑time memory tables and offline disk tables.

Big DataData EngineeringETL

0 likes · 13 min read

Performance Platform: Accelerating Data Production and Consumption

Baidu Geek Talk

Mar 6, 2023 · Big Data

Accelerating Data Production and Consumption in Baidu's Performance Platform

Baidu's Performance Platform speeds data production and consumption by adopting a unified stream‑batch architecture with TM and Spark, leveraging the Turing warehouse, introducing tiered service grading, robust governance and compliance measures, and offering self‑service analytics, cutting latency from minutes or days to milliseconds while handling billions of daily records and boosting SLA adherence, data accuracy, and user satisfaction.

Big DataData EngineeringReal-time Processing

0 likes · 12 min read

Accelerating Data Production and Consumption in Baidu's Performance Platform

GuanYuan Data Tech Team

Feb 16, 2023 · Big Data

How the Modern Data Stack Transforms BI & AI: From Legacy Warehouses to Cloud‑Native Analytics

This article traces the evolution of the modern data stack, explaining the shortcomings of traditional data warehouses, the rise of cloud‑native ELT, self‑service analytics, analytics‑as‑software, and enhanced decision intelligence, while highlighting emerging trends and practical implementations.

BIDataOpsanalytics

0 likes · 15 min read

How the Modern Data Stack Transforms BI & AI: From Legacy Warehouses to Cloud‑Native Analytics

DataFunSummit

Dec 10, 2022 · Big Data

Applying Apache Spark in Guanyuan Self-Service Analytics System: Architecture, Challenges, and Solutions

This presentation details how Guanyuan Data leverages Apache Spark within its self‑service analytics platform, covering product features, flexible deployment, resource isolation, performance challenges, architectural solutions, and future cloud‑native enhancements to support thousands of users and massive query workloads.

Apache SparkBig DataResource Scheduling

0 likes · 14 min read

Applying Apache Spark in Guanyuan Self-Service Analytics System: Architecture, Challenges, and Solutions

Zhuanzhuan Tech

Dec 7, 2022 · Databases

ClickHouse in Self‑Service Analytics: OLAP Selection, Platform Architecture, Optimization Practices, and Future Outlook

This article examines the selection of ClickHouse as the OLAP engine for a self‑service analytics platform, describes the platform’s architecture, details memory and performance tuning techniques, discusses large‑scale join handling, and outlines current challenges and future development directions for ClickHouse.

Big DataClickHouseOLAP

0 likes · 12 min read

ClickHouse in Self‑Service Analytics: OLAP Selection, Platform Architecture, Optimization Practices, and Future Outlook

DataFunSummit

Sep 10, 2022 · Big Data

Application of Multi‑Dimensional Analysis in NetEase Cloud Music's Social Innovation Business

The talk explains how NetEase Cloud Music leverages multi‑dimensional analysis across its social innovation apps, detailing business background, use‑case scenarios, technology choices, data‑platform architecture, and future plans to enable self‑service analytics and improve data efficiency.

Big DataCloud MusicData Warehousing

0 likes · 12 min read

Application of Multi‑Dimensional Analysis in NetEase Cloud Music's Social Innovation Business

DataFunTalk

Nov 20, 2021 · Big Data

How to Build a Big Data Platform from Zero to One: Architecture, Components, and Best Practices

This article provides a comprehensive guide to designing and implementing a big‑data platform, covering architecture overview, data ingestion with Flume, storage on HDFS/Hive/HBase, processing engines such as Hive, Spark and Flink, scheduling solutions like Azkaban and Airflow, and the construction of self‑service analytics systems.

Big DataData EngineeringETL

0 likes · 29 min read

How to Build a Big Data Platform from Zero to One: Architecture, Components, and Best Practices

37 Interactive Technology Team

Mar 28, 2019 · Big Data

Approaches to Building a Basic Data Platform

To handle terabytes of daily data and diverse business needs, the company built a three‑layer basic data platform—collection/computation/storage, unified data management, and API‑driven services—augmented by a standardized collection system, a robust Domino scheduler, and a self‑service analysis tool, aiming to evolve into a full data‑middle‑office for end‑to‑end intelligence.

Big DataSchedulingdata integration

0 likes · 8 min read

Approaches to Building a Basic Data Platform