Articles.
In 2016, DEV3LOPCOM, LLC began sharing informative articles and technical tutorials about software, methodologies, research and programming languages. Our articles are designed to be accessible and informative, drawing readers interested in solving technical problems and understanding concepts. Dive into our collection to learn how these technical articles may benefit you. Click a button transition to the content or start with a recent read.
Recent Articles
Data Sharing Agreements: Technical Implementation Guide
In the modern landscape, data reigns supreme, powering everything from analytical insights and strategic decisions to innovative customer experiences. Effective data sharing agreements (DSAs) act as the traffic lights governing your data highways, ensuring every byte...
Business Glossary Integration with Technical Metadata
In today's increasingly data-driven world, clarity and accuracy are paramount. Data forms the backbone of strategic decisions, guiding business leaders through an ever-changing landscape of technology and innovation. Yet, with mounting volumes of data and growing...
Data Catalog Federation Across Multiple Tools
In today's data-driven landscape, enterprises are often managing multiple data platforms, each harboring crucial insight yet isolated in distinct silos. This complexity demands smarter strategies for data integration, accessibility, and governance, fueling a rapidly...
Regulatory-Driven Data Classification Framework
In an era shaped by expanding digital interactions, regulations on data management continue to evolve in rigor and complexity. As decision-makers within the fast-paced fields of data analytics, software development, or digital innovation, staying ahead in managing...
Statistical Disclosure Control Implementation Techniques
In the data-driven era of rapid digital transformation, protecting sensitive information is as pivotal as harnessing its analytical potential. Whether you're an executive steering strategy in healthcare, a data professional exploring market insights, or an innovator...
Identity Graph Construction for Customer Data Integration
In an ever-evolving landscape, harnessing customer data has become the foundation of meaningful interactions, business intelligence, and strategic decision-making. Yet, despite possessing vast amounts of data, many organizations struggle to achieve a cohesive,...
Automated Data Sensitivity Classification Using ML
In an era where data-driven decisions power innovative business strategies and insights, protecting sensitive information becomes mission-critical. Modern enterprises collect and handle vast quantities of data that range from openly accessible public information to...
Data Deletion Verification and Certification Process
In today's hyper-connected digital landscape, data has become the lifeblood of organizations across all industries. With its sheer volume and complexity, managing data responsibly has never been more critical—or more challenging. Enterprises must now grapple with...
Cross-Border Data Transfer Technical Controls
In our rapidly digitizing economy, organizations regularly move data beyond geographical borders to fuel global collaboration and innovation. However, cross-border data transfers introduce critical technical and compliance risks that must be effectively managed....
Data Consumer Registration and Notification System
In the fast-paced world of data-driven decision making, businesses that maximize their data value gain strategic advantages over competitors. Yet, effectively distributing and managing data across numerous stakeholders swiftly becomes a daunting challenge. Enter the...
External Reference Data Integration Architecture
In today's rapidly evolving business environment, data integration emerges as the backbone of making informed and strategic decisions. External reference data, which includes anything from market trends, geographical codes, regulatory changes, to standardized industry...
Master Data Management System Integration Patterns
In today’s digital economy, data stands as a catalyst for innovation and competitive advantage. Enterprises grapple daily with exponential data growth, diverse data sources, and ensuring data integrity across organizational silos. Effective Master Data Management...
Data Element Genealogy Tracing Across Systems
In a technology ecosystem rich with complexity, data acts as an organization's digital lifeblood—flowing, evolving, and connecting each system, process, and stakeholder. Yet, as data assets scatter across cloud applications, data lakes, analytics tools, and legacy...
Inference Attack Prevention in Published Datasets
In an age driven by data-driven insights, the value of published datasets cannot be overstated. Yet, as organizations increasingly open their data gateways to innovation and analytics-driven strategies, the risk of inference attacks looms larger than ever. These...
Metadata-Driven Default Security Classification
In today's digital landscape, organizations face an ever-growing challenge to safeguard their data without stifling agility and innovation. Data, rightly considered the lifeblood of modern enterprises, holds unmatched power coupled with significant risks when handled...
Orphaned Data Detection and Management Framework
In today's rapidly evolving digital landscape, immense volumes of data constantly flow through enterprise systems—from cloud storage platforms and analytics pipelines to legacy databases. However, an overlooked but critical issue that emerges amidst this influx of...
Confidentiality Classification Inheritance Rules
The digital age has ushered organizations into unprecedented growth fueled by data-driven decisions. Yet, as data volumes escalate, enterprises face increasingly complex challenges managing sensitive information. Understanding and applying robust confidentiality...
Purpose-Limitation Enforcement in Data Usage
In today's data-driven economy, organizations continuously strive to leverage data for innovation and decision-making. Yet, this potential often collides with concerns around privacy, compliance, and responsible data use. Purpose-limitation—the core principle that...
Business Term to Technical Implementation Mapping Repository
In today's fast-paced digital economy, aligning strategic business concepts with the right technological execution is critical. Too often, businesses witness a gap between visionary terms and their corresponding technological implementation, causing delays,...
Self-Service Data Access Request Workflow Implementation
As organizations grow more data-centric, the pressure on IT and analytics teams to rapidly provision data access can become overwhelming. Decision-makers increasingly require instant insights, and a backlog or delay in granting data access requests can dramatically...
Enterprise Data Model Versioning and Deployment
Organizations today face unprecedented challenges and opportunities in handling large-scale, evolving data models. Every data-driven business understands that reliable, timely data fuels better decisions, which directly impact growth and innovation. Yet, managing...
Metadata Exchange Standards Implementation (DCAT, etc.)
In the rapidly evolving digital economy, clear, consistent, and effective data exchange is no longer optional—it's critical. Data-driven organizations across sectors require efficient communication about their datasets to streamline operations, improve collaboration,...
Regulatory Reporting Field Mapping and Lineage
In today's highly regulated business environments, precision in managing data is no longer optional; it’s a cornerstone of successful compliance and sound decision-making. Organizations face immense pressure to ensure their data is accurate, secure, and transparent...
Data Sharing Sandbox Environment Architecture
In today's data-driven business ecosystem, innovative companies recognize that securely sharing data for analytics and collaboration is no longer mere aspiration—it’s an operational necessity. Creating a well-architected data sharing sandbox environment positions your...
How to Transition from Traditional ETL to Modern Data Engineering
Businesses today live and breathe data, needing access not just to raw information but sophisticated insights that strategically empower decisions. Historically, companies relied on traditional Extract, Transform, Load (ETL) processes to develop data analytics...
Uncertainty Visualization Techniques for Statistical Data
In today's rapidly evolving data-driven world, statistics and analytics lead the way, guiding insight, innovation, and strategic decision-making. Yet, behind every data point lies inherent uncertainty—variables that can cloud judgment, complicate interpretation, and...
Perceptual Edge Detection in Chart Design
In today's fast-paced data-driven world, interpreting visual information quickly and accurately can be the difference between strategic success and missed opportunities. As decision-makers, we rely heavily on visual insights to shape strategies, understand customer...
Interactive Brushing and Linking in Multi-View Dashboards
In today’s data-driven world, dashboards aren’t just static summaries—they're dynamic, interactive canvases, empowering decision-makers to explore insights visually and intuitively. Specifically, combining interactive brushing and linking in multi-view dashboards...
Typography Best Practices for Data-Dense Displays
In today's data-intensive environment, decision-makers increasingly rely on complex visual tools and dashboards to harness analytics, extract insights, and drive strategic choices. Yet, even the most sophisticated data can become obscured and misunderstood if the...
Radial Visualization Techniques for Cyclical Data Patterns
In the digital age, businesses increasingly grapple with datasets characterized by cyclical patterns—data fluctuating over regular intervals, such as hourly website traffic, seasonal sales performance, or monthly system loads. As decision-makers, interpreting these...
Automation
The benefits of using ETL in data warehousing.
ETL, or Extract, Transform, and Load, is a process used in data warehousing to extract data from various sources, transform it into a format that can be loaded into a target system or data warehouse, and then load it into the target system. This process is useful...
A beginner’s guide to ETL (Extract, Transform, Load).
ETL is a process in data warehousing that involves extracting data from various sources, transforming it into a format that is suitable for analysis, and loading it into a target database or data warehouse. This process is commonly used to integrate data from multiple...
Solution: The ability to connect to Google Sheets greater than 10 MB is currently not built into the product.
When building a data source on Google Sheets in Tableau Desktop 10mb is the max per Google Sheet. However, what if we could connect to more than one Google Sheet at the same time? Google Sheets works wonders with Tableau Public because it allows...
Business
Spotting Patterns: How Machine Learning Enhances Fraud Detection
Fraud detection is no longer just about reacting to incidents; it’s about predicting and preventing them before they escalate. At the heart of this proactive approach is machine learning (ML)—a powerful tool that enables systems to spot patterns and anomalies in ways...
The Role of Data Streaming, Stopping Fraud Before It Happens
Fraud detection is no longer about reacting after the damage is done—it’s about prevention, powered by real-time insights. With open-source tools like WebSockets and Node.js, businesses can build scalable, efficient fraud detection systems without breaking the bank....
What Is a Semantic Layer and Why Should You Care? 🚀
We encounter a common challenge: a company with a lot of truth in spreadsheets, and often desperately in need of a semantic layer. This is a common scenario for even powerful enterprises. Picture this—a fast-growing e-commerce company tracking every critical metric in...
TableauHelp
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Solutions
Multi-Modal Sensory Analytics: Integrating Audio, Visual, and Text Data
Decision-makers are continually tasked with deriving deeper insights from increasingly complex data streams. While traditional analytics often focus purely on standard numeric datasets, modern competitive organizations understand the strategic value of integrating...
Designing Effective Data Team Structures
Strategically structuring your data teams isn't just about having the right people in the room; it's a meticulous exercise in orchestrating collaboration, defining clear roles, and laying down solid frameworks. In today's data-intensive marketplace, businesses that...
How to Scale Your Data Infrastructure as You Grow
In today's data-driven landscape, your company's infrastructure isn't just a backend utility—it's the foundational backbone that determines your organization's growth trajectory and sustainability. As your business expands, so does the volume, velocity, and variety of...
SQL
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