BestHub
Sign in
Tagged articles
559 articles
Page 6 of 6
Youzan Coder
Youzan Coder
Jan 20, 2021 · Information Security

How Youzan Built a Scalable Big Data Security Framework for Privacy Protection

This article details Youzan's end‑to‑end big data security architecture, covering data lifecycle protection, classification, access control, auditing, backup, privacy safeguards, sensitive data detection, masking strategies, and compliance processes to ensure secure and compliant data handling across the platform.

Data Privacybig data securitydata governance
0 likes · 18 min read
How Youzan Built a Scalable Big Data Security Framework for Privacy Protection
Architects Research Society
Architects Research Society
Jan 13, 2021 · Fundamentals

Master Data Management (MDM): Concepts, Business Value, Technical Challenges, and Architectural Considerations

The article explains master data management (MDM) as a framework for creating a single, reliable source of truth, outlines its growing business relevance, discusses key technical challenges such as data governance and scalability, and explores next‑generation architectures involving graph databases, big data, and machine learning.

Big DataGraph DatabaseMaster Data Management
0 likes · 10 min read
Master Data Management (MDM): Concepts, Business Value, Technical Challenges, and Architectural Considerations
ITPUB
ITPUB
Jan 12, 2021 · Databases

What the Latest DTCC Conference Reveals About the Future of Databases

The DTCC conference recap explores emerging data trends, multi‑model databases, governance frameworks, architecture migrations, NewSQL and MySQL high‑availability, distributed transaction challenges, AI‑driven operations, data middle‑platform debates, cloud‑native storage‑compute separation, and comprehensive data security across the full data lifecycle.

Cloud ComputingData SecurityDistributed Systems
0 likes · 19 min read
What the Latest DTCC Conference Reveals About the Future of Databases
Architects Research Society
Architects Research Society
Jan 11, 2021 · Fundamentals

Top Reasons Why MDM Implementations Fail

This article examines the common pitfalls that cause Master Data Management (MDM) projects to fail, including underestimating effort, insufficient resources, overly ambitious scope, lack of data governance, excessive rules, and inadequate executive support, offering practical insights for successful implementation.

Enterprise DataImplementation ChallengesMDM
0 likes · 12 min read
Top Reasons Why MDM Implementations Fail
Youzan Coder
Youzan Coder
Dec 25, 2020 · Big Data

Metadata Governance and Collection in a Data Asset Platform

The platform implements comprehensive metadata governance by extracting, standardizing, and ingesting basic, trend, resource, lineage, and task metadata from offline and real‑time systems via a Kafka‑based SDK, enabling unified storage, monitoring, alerts, and future automation to improve data asset visibility and quality.

Big DataMonitoringSDK
0 likes · 18 min read
Metadata Governance and Collection in a Data Asset Platform
ITFLY8 Architecture Home
ITFLY8 Architecture Home
Dec 18, 2020 · Big Data

Unlocking the Data Middle Platform: From Ingestion to Real‑Time Analytics

This article provides a comprehensive overview of data middle platform concepts, covering data aggregation, collection tools, development modules, job scheduling, baseline control, heterogeneous storage, permission management, real‑time and offline processing, governance, services, and implementation details for building robust big‑data solutions.

Data PlatformETLFlink
0 likes · 25 min read
Unlocking the Data Middle Platform: From Ingestion to Real‑Time Analytics
Alibaba Cloud Developer
Alibaba Cloud Developer
Dec 7, 2020 · Big Data

How to Build a New‑Retail Data Middle Platform with DataWorks

This article explains how new‑retail companies can design and implement a data middle platform using Alibaba Cloud's DataWorks, covering business model analysis, technical architecture, layer‑by‑layer data modeling, governance, security, and the concrete benefits of turning raw data into actionable business insights.

Big Data ArchitectureData Middle PlatformData Security
0 likes · 28 min read
How to Build a New‑Retail Data Middle Platform with DataWorks
DataFunTalk
DataFunTalk
Nov 24, 2020 · Artificial Intelligence

Building Next‑Generation Data Intelligence Infrastructure with Knowledge Graphs: From New Infrastructure to Cognitive AI Platforms

This presentation explains how knowledge graphs serve as the foundation for new‑infrastructure initiatives, detailing the evolution of AI from perception to cognition, the role of big‑data centers, DIKW modeling, intelligent data governance, and the construction of a cognitive AI middle‑platform for industry applications.

AI infrastructureArtificial IntelligenceBig Data
0 likes · 18 min read
Building Next‑Generation Data Intelligence Infrastructure with Knowledge Graphs: From New Infrastructure to Cognitive AI Platforms
Beike Product & Technology
Beike Product & Technology
Nov 13, 2020 · Big Data

Beike One‑Stop Big Data Development Platform: Architecture, Evolution, and Future Outlook

The article summarizes Beike's one‑stop big data development platform, describing its data business background, the evolution from a simple Hadoop‑Kafka‑Hive stack to a metadata‑driven, asset‑oriented platform, and outlines current capabilities in data management, integration, scheduling, quality, openness, and future plans.

Big DataData PlatformETL
0 likes · 11 min read
Beike One‑Stop Big Data Development Platform: Architecture, Evolution, and Future Outlook
DataFunTalk
DataFunTalk
Oct 7, 2020 · Big Data

Yanxuan Data Warehouse: Architecture, Standards, and Evaluation Framework

This article outlines the Yanxuan data warehouse’s layered architecture, the offline and real‑time development platforms, the comprehensive standards for metric definition, model design, and SQL development, and proposes a six‑dimensional evaluation system covering data norms, security, quality, stability, continuous improvement, and development efficiency.

Big DataSQL Standardsdata engineering
0 likes · 12 min read
Yanxuan Data Warehouse: Architecture, Standards, and Evaluation Framework
DataFunTalk
DataFunTalk
Sep 25, 2020 · Big Data

Meituan Waimai Data Warehouse: Architecture Evolution, Governance, and Future Roadmap

The article details Meituan Waimai's offline data warehouse evolution from its initial V1.0 design through V2.0 improvements to the V3.0 modeling‑tool driven architecture, covering the four‑layer framework, Spark‑based ETL, data governance processes, resource optimization, security measures, and future development plans.

Big DataETLMeituan
0 likes · 22 min read
Meituan Waimai Data Warehouse: Architecture Evolution, Governance, and Future Roadmap
Ctrip Technology
Ctrip Technology
Sep 10, 2020 · Big Data

Design and Implementation of a Unified Log Framework for Ctrip Payment Center

The article describes the design, architecture, and operational details of a unified logging framework at Ctrip's payment center, covering log production via a Log4j2 extension, Kafka‑Camus collection, Hive/ORC storage, MapReduce parsing optimizations, and governance strategies for massive daily TB‑scale data.

Big DataCamusHadoop
0 likes · 15 min read
Design and Implementation of a Unified Log Framework for Ctrip Payment Center
Didi Tech
Didi Tech
Aug 27, 2020 · Big Data

Building and Managing an Indicator System: Methodology, Models, and Practices

The article defines an indicator system as a structured set of interrelated metrics and dimensions, explains its lifecycle and hierarchy, presents OSM and AARRR models for construction, details metadata and dimension management, addresses business‑technical challenges, outlines a roadmap for implementation, and showcases DiDi’s deployment of thousands of indicators across dozens of domains.

AARRRIndicator SystemOSM model
0 likes · 19 min read
Building and Managing an Indicator System: Methodology, Models, and Practices
StarRing Big Data Open Lab
StarRing Big Data Open Lab
Aug 24, 2020 · Big Data

How to Master Data Quality Management in the Big Data Era

This article explores the concept of data quality, identifies ten common root causes, presents a comprehensive data quality management framework, outlines evaluation methods and key dimensions, and discusses future challenges and tools for improving data quality in large‑scale data environments.

Data Managementdata governancedata quality
0 likes · 16 min read
How to Master Data Quality Management in the Big Data Era
Suning Technology
Suning Technology
Aug 14, 2020 · Big Data

Building SuNing’s Supply‑Chain Data Platform with DDD and Big‑Data Design

This article recounts SuNing’s step‑by‑step journey of designing and implementing a supply‑chain data middle platform, outlining its business rationale, DDD‑based domain modeling, layered system architecture, and practical deployment insights that illustrate how a tailored big‑data solution can enhance data services and governance.

Big DataDDDData Platform
0 likes · 11 min read
Building SuNing’s Supply‑Chain Data Platform with DDD and Big‑Data Design
Architects' Tech Alliance
Architects' Tech Alliance
Aug 11, 2020 · Big Data

Comprehensive Overview of Data Middle Platform Architecture, Components, and Practices

This article provides an extensive summary of data middle platform concepts, covering data aggregation, collection tools, offline and real‑time development, data governance, service layers, warehouse construction, and operational practices, illustrating how enterprises build and manage a unified data ecosystem.

Big DataData Middle PlatformData Warehouse
0 likes · 27 min read
Comprehensive Overview of Data Middle Platform Architecture, Components, and Practices
Ctrip Technology
Ctrip Technology
Aug 6, 2020 · Big Data

Data Governance Practices and Model Design in Ctrip Vacation Data Warehouse

This article shares the practical experience and thinking behind Ctrip's vacation data governance project, covering team efficiency optimization, demand sorting, data domain definition, warehouse layering, unified dimension modeling, metric standardization, and the overall benefits of a centralized data governance framework.

Big DataCtripData Warehouse
0 likes · 17 min read
Data Governance Practices and Model Design in Ctrip Vacation Data Warehouse
Amap Tech
Amap Tech
Jul 23, 2020 · Big Data

Overview of Apache Big Data Ecosystem Tools

The article surveys the Apache big‑data ecosystem, covering Hadoop’s storage and resource management, column stores HBase and Kudu, compute engines Spark, Flink, Impala, and Presto, coordination via ZooKeeper, ingestion with Sqoop and Flume, messaging Kafka, security Ranger and Sentry, metadata Atlas, OLAP Kylin, Hive, quality tool Griffin, notebooks Zeppelin, visualizations Superset and Tableau, the TPCx‑BB benchmark, and ends with an Alibaba analysis competition notice.

AnalyticsApacheDistributed Systems
0 likes · 19 min read
Overview of Apache Big Data Ecosystem Tools
Architects Research Society
Architects Research Society
Jun 16, 2020 · Information Security

Information Governance: Roles, Responsibilities, and Key Processes

Information governance is a program that ensures enterprise data accuracy, completeness, consistency, accessibility, and security by establishing business‑driven roles such as a data governance committee, data stewards, and data custodians, and by defining key responsibilities, processes, and metrics for data quality, privacy, and compliance.

Enterprise Data ManagementInformation Securitydata governance
0 likes · 11 min read
Information Governance: Roles, Responsibilities, and Key Processes
TAL Education Technology
TAL Education Technology
Jun 11, 2020 · Big Data

Data Quality Monitoring: Standards, Practices, and Technical Solutions

This article outlines the importance of data quality in the big‑data era, defines evaluation criteria such as integrity, accuracy, consistency and timeliness, describes daily monitoring and reconciliation processes, and proposes technical solutions and challenges for building a comprehensive data‑quality monitoring platform.

Data WarehouseOperationsdata governance
0 likes · 7 min read
Data Quality Monitoring: Standards, Practices, and Technical Solutions
Big Data Technology & Architecture
Big Data Technology & Architecture
May 20, 2020 · Big Data

Technical Overview of Real-time Data Platform (RTDP) Architecture and Component Selection

This article presents a comprehensive technical overview of the Real-time Data Platform (RTDP), detailing its overall architecture, component selection—including DBus, Kafka, Wormhole, Moonbox, and Davinci—design philosophies, functional features, and various deployment patterns such as synchronous, stream-processing, rotation, and intelligent modes.

data governancedata integration
0 likes · 26 min read
Technical Overview of Real-time Data Platform (RTDP) Architecture and Component Selection
dbaplus Community
dbaplus Community
Apr 26, 2020 · Big Data

Evolving from Data Warehouses to Data Middle Platforms: Architecture & Practices

This talk reviews China's big‑data evolution from early enterprise data warehouses to modern data middle platforms, outlines core architectural components, technology selections, data development practices, lifecycle and quality management, and shares practical Q&A insights for building scalable, cost‑effective data infrastructures.

Big DataData ArchitectureData Middle Platform
0 likes · 28 min read
Evolving from Data Warehouses to Data Middle Platforms: Architecture & Practices
Youzan Coder
Youzan Coder
Mar 18, 2020 · Big Data

The Evolution of Youzan’s Data Warehouse in a Big Data Environment

The article traces Youzan’s data warehouse from its chaotic early days lacking structure, through a 2016 Airflow‑driven construction phase that introduced layered ODS/DW/Data Mart architecture and naming standards, to a mature stage focused on efficiency, security, SparkSQL, dimensional modeling, metadata, and ongoing real‑time and governance challenges.

AirflowBig DataData Warehouse
0 likes · 20 min read
The Evolution of Youzan’s Data Warehouse in a Big Data Environment
Meituan Technology Team
Meituan Technology Team
Mar 12, 2020 · Big Data

Data Governance Practices in Meituan Delivery: Architecture, Standards, and Security

Meituan Delivery’s data‑governance framework combines a four‑layer warehouse architecture with comprehensive business, technical, security, and resource‑management standards, continuous metadata and security controls, and tools such as Wherehows and QuickSight, delivering standardized, secure, and easily shareable data while guiding future optimization and emerging‑technology adoption.

Big DataData ArchitectureData Security
0 likes · 27 min read
Data Governance Practices in Meituan Delivery: Architecture, Standards, and Security
Big Data Technology & Architecture
Big Data Technology & Architecture
Dec 7, 2019 · Big Data

Understanding Data Middle Platform: Definition, Construction, Product Selection, and Case Studies

This article explains what a data middle platform is, outlines its construction process, discusses how to choose suitable products, and presents enterprise case studies, offering a comprehensive guide to building and leveraging a data middle platform for big‑data initiatives.

Big Data ArchitectureData Middle PlatformData Platform
0 likes · 5 min read
Understanding Data Middle Platform: Definition, Construction, Product Selection, and Case Studies
dbaplus Community
dbaplus Community
Oct 27, 2019 · Product Management

What Skills Do Data Product Managers Need in a Data Middle Platform?

The article explains the concept of a data middle platform, why it matters for rapid demand response and resource integration, and outlines the distinct responsibilities and required skill sets of data product managers and data platform product managers within such ecosystems.

Data ArchitectureData Middle PlatformData Product
0 likes · 11 min read
What Skills Do Data Product Managers Need in a Data Middle Platform?
Meituan Technology Team
Meituan Technology Team
Oct 17, 2019 · Big Data

OneData Methodology: Building a Unified Data Warehouse Architecture and Governance Framework

By adapting Alibaba’s OneData methodology, the project establishes a unified data‑warehouse architecture, standards, and governance framework—including consolidated business intake, standardized design layers, naming conventions, and delivery metrics—that resolves data‑quality issues, enhances scalability and reusability, and delivers faster, reliable data support for evolving business needs.

Big DataData ArchitectureData Warehouse
0 likes · 15 min read
OneData Methodology: Building a Unified Data Warehouse Architecture and Governance Framework
vivo Internet Technology
vivo Internet Technology
Jul 29, 2019 · Big Data

Is Hadoop Dead? An Analysis of Cloudera’s Move Toward an Enterprise Data Cloud

While Hadoop remains a powerful but complex batch‑processing engine, Cloudera’s merger with Hortonworks and its pivot toward an enterprise data cloud—offering hybrid, multi‑cloud analytics, security, and governance—signals a strategic shift that keeps Hadoop relevant yet no longer central amid rising competitors like MongoDB and Elasticsearch.

Cloud ComputingClouderaEnterprise Data Cloud
0 likes · 10 min read
Is Hadoop Dead? An Analysis of Cloudera’s Move Toward an Enterprise Data Cloud
Dada Group Technology
Dada Group Technology
Jun 11, 2019 · Big Data

Building and Evolving the Dada‑JD Daojia Big Data Platform: Architecture, Strategies, and Lessons Learned

This article presents a comprehensive case study of the Dada‑JD Daojia big data platform, detailing its evolution from a MySQL‑based warehouse to a multi‑layered One Data, One Platform, One Service, Many Apps architecture, the technical challenges faced, and the strategic approaches adopted to ensure coverage, accuracy, stability, and scalability.

Big DataData PlatformData Warehouse
0 likes · 14 min read
Building and Evolving the Dada‑JD Daojia Big Data Platform: Architecture, Strategies, and Lessons Learned
Qunar Tech Salon
Qunar Tech Salon
Apr 12, 2019 · Big Data

Understanding the Data Middle Platform: Concepts, Benefits, Challenges, and Implementation

The article explains what a data middle platform is, why it differs from data warehouses and data platforms, outlines its core capabilities, discusses the strategic and tactical considerations for building one, and examines the organizational, technical, and privacy challenges involved in its adoption.

Data Middle PlatformEnterprise Architecturedata API
0 likes · 23 min read
Understanding the Data Middle Platform: Concepts, Benefits, Challenges, and Implementation
dbaplus Community
dbaplus Community
Mar 11, 2019 · Operations

How a Bank Built a Tiered CMDB for Scalable, Secure Operations

This article details a bank’s practical experience designing and implementing a hierarchical CMDB, covering architecture, data standards, lifecycle management, accuracy controls, query visualization, performance tuning, and real‑world use cases for daily operations and private‑cloud management.

CMDBConfiguration ManagementIT Operations
0 likes · 14 min read
How a Bank Built a Tiered CMDB for Scalable, Secure Operations
Architects' Tech Alliance
Architects' Tech Alliance
Mar 4, 2019 · Big Data

Understanding the Data Middle Platform: Concepts, Benefits, and Implementation Guidelines

The article explains the emergence of data middle platforms in the era of digital and intelligent transformation, defines their architecture and functions, outlines four key reasons for building them—including data reuse, AI enablement, innovation acceleration, and talent development—and provides practical principles for successful implementation.

Data Middle Platformdata governance
0 likes · 9 min read
Understanding the Data Middle Platform: Concepts, Benefits, and Implementation Guidelines
AntTech
AntTech
Feb 27, 2019 · Big Data

Ant Financial Data Governance: Practices and Challenges in Data Quality Management

The article details Ant Financial’s comprehensive data quality governance framework, covering its architecture, challenges, implementation strategies, and real‑world case studies, illustrating how the company integrates data monitoring, AI‑driven self‑healing, and rigorous release controls to ensure high‑quality data across its platform.

Ant FinancialBig DataData Platform
0 likes · 17 min read
Ant Financial Data Governance: Practices and Challenges in Data Quality Management
JD Tech Talk
JD Tech Talk
Jan 10, 2019 · Artificial Intelligence

Sensitive Field Identification Using Wide & Deep and TextCNN Models

This article presents a machine‑learning approach for detecting sensitive data fields in a data warehouse by combining a Wide & Deep network with a TextCNN architecture, detailing data exploration, model design, training strategies, performance results, and deployment workflow.

TextCNNWide&Deepdata governance
0 likes · 9 min read
Sensitive Field Identification Using Wide & Deep and TextCNN Models
Didi Tech
Didi Tech
Dec 26, 2018 · Industry Insights

How Didi Implements Full‑Chain Data Tiered Protection for Reliable Operations

Facing growing data‑driven pressures, Didi designed a full‑link data tiered protection framework that defines classification standards, integrates data levels across the entire pipeline, and applies concrete safeguards and tooling to improve resource allocation, backup reliability, and overall data reliability.

Big DataDidiIndustry Insights
0 likes · 7 min read
How Didi Implements Full‑Chain Data Tiered Protection for Reliable Operations
Efficient Ops
Efficient Ops
Oct 24, 2018 · Artificial Intelligence

How AIOps Transforms IT Operations: Real‑World Solutions and Challenges

This article explains the evolution of AIOps, outlines the data‑governance and integration challenges faced by large‑scale IT environments, and presents a step‑by‑step solution architecture—including algorithms, multi‑dimensional views, and role‑based workflows—to enable intelligent, automated operations.

aiopsdata governance
0 likes · 24 min read
How AIOps Transforms IT Operations: Real‑World Solutions and Challenges
Architect's Tech Stack
Architect's Tech Stack
Oct 23, 2018 · Fundamentals

Common Data Collection Challenges in Startups and Practical Solutions

The article examines three typical data collection problems faced by startups—unclear collection methods, chaotic tracking points, and poor collaboration between data and engineering teams—and offers practical strategies such as adopting full‑event models, appointing data architects, and securing top‑down support to achieve reliable, comprehensive analytics.

AnalyticsStartupdata collection
0 likes · 10 min read
Common Data Collection Challenges in Startups and Practical Solutions
360 Tech Engineering
360 Tech Engineering
Aug 7, 2018 · Big Data

Evolution and Practice of 360 Big Data Center Platform

The article presents a comprehensive overview of 360's Big Data Center evolution, covering business background, platform‑as‑a‑service architecture, data asset management, user‑profile unification, platform milestones, technical architecture, performance optimizations, online query capabilities, future plans, and a Q&A session.

360Data Platformarchitecture
0 likes · 22 min read
Evolution and Practice of 360 Big Data Center Platform
Big Data and Microservices
Big Data and Microservices
Aug 6, 2018 · Fundamentals

What Is Master Data and How Does Master Data Management Transform Enterprises?

Master data refers to high‑value core business entities such as customers, products, and accounts that are shared across multiple systems, and master data management (MDM) provides the standards, technologies, and processes to collect, integrate, cleanse, govern, and distribute this data consistently throughout an organization, improving data quality, compliance, and agility.

Data ManagementEnterprise ArchitectureMDM
0 likes · 7 min read
What Is Master Data and How Does Master Data Management Transform Enterprises?
Meituan Technology Team
Meituan Technology Team
Mar 22, 2018 · Big Data

DataMan: A Data Quality Governance Platform for Meituan's Big Data Ecosystem

Meituan’s DataMan platform provides a unified, closed‑loop data‑quality governance solution that collects demand, refines rules, executes monitoring across offline and real‑time jobs, tracks issues, and builds a knowledge base, improving completeness, accuracy, consistency, and timeliness while optimizing storage, reducing fault resolution time, and supporting data‑driven decisions.

Data WarehousePlatformdata governance
0 likes · 17 min read
DataMan: A Data Quality Governance Platform for Meituan's Big Data Ecosystem
Alibaba Cloud Developer
Alibaba Cloud Developer
Oct 15, 2017 · Information Security

How Alibaba’s Data Security Maturity Model (DSMM) Is Shaping China’s Data Protection Landscape

The article explains Alibaba's Data Security Maturity Model (DSMM), its partnership program, the involvement of 17 leading security firms, and how the model aims to improve data security capabilities across industries by establishing standardized assessment criteria and fostering ecosystem collaboration.

AlibabaBig DataDSMM
0 likes · 10 min read
How Alibaba’s Data Security Maturity Model (DSMM) Is Shaping China’s Data Protection Landscape
21CTO
21CTO
Jul 22, 2017 · Big Data

Why Every Company Needs a Chief Data Officer to Unlock Data Value

The article explains the strategic importance of the Chief Data Officer role, outlining how CDOs drive data‑driven innovation through a four‑stage data supply chain—data supply, logistics, science, and execution—to create competitive advantage and business growth.

Big DataChief Data OfficerData Management
0 likes · 14 min read
Why Every Company Needs a Chief Data Officer to Unlock Data Value
StarRing Big Data Open Lab
StarRing Big Data Open Lab
May 27, 2017 · Big Data

Simplify Big Data Governance with Data Lineage & Impact Analysis

Enterprise big‑data platforms face massive scale and complex metadata relationships, but using Transwarp Governor’s data lineage and impact analysis graphs enables precise tracing of data origins, rapid error localization, and prediction of downstream effects, dramatically improving data quality and governance efficiency.

Big DataData LineageTranswarp Governor
0 likes · 8 min read
Simplify Big Data Governance with Data Lineage & Impact Analysis
ITPUB
ITPUB
Jul 19, 2016 · Big Data

From Traditional Data Warehouses to Big Data: Practical Techniques and Migration Insights

The talk shares hands‑on experiences and best‑practice methods for traditional data‑warehouse processing, public and behavioral data handling in big‑data environments, and practical guidance for migrating legacy warehouses to modern Hadoop‑based platforms, emphasizing data governance, security, and performance optimization.

Big DataData WarehouseETL
0 likes · 13 min read
From Traditional Data Warehouses to Big Data: Practical Techniques and Migration Insights
dbaplus Community
dbaplus Community
Dec 4, 2015 · Big Data

Big Data Insights from the 2015 Internet+ Summit: Advertising, Finance & Security

The article compiles detailed notes from the 2015 Internet+ Big Data Summit, highlighting how data monetization reshapes advertising, drives financial analytics, improves operational efficiency, and strengthens security, while presenting real‑world case studies, models, and practical recommendations from industry experts.

AdvertisingData MonetizationFinance
0 likes · 17 min read
Big Data Insights from the 2015 Internet+ Summit: Advertising, Finance & Security
Efficient Ops
Efficient Ops
Jul 4, 2015 · Databases

Why Early Database Management Standards Save You Hundreds of Hours

This article explains when to introduce database usage standards, how to implement them effectively, the benefits they bring, and the challenges of enforcement, illustrated with real‑world examples, code snippets, and a Q&A session with a senior DBA.

DBA PracticesDatabase StandardsOperational Efficiency
0 likes · 12 min read
Why Early Database Management Standards Save You Hundreds of Hours