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 Element Collision Detection in Enterprise Integration
In a bustling digital ecosystem, data flows freely across numerous applications, systems, and platforms. Business leaders understand well the critical need to preserve data integrity and harmonious integration as their organization scales. Imagine data streams as...
Semantic Versioning for Data Schemas and APIs
In today’s rapidly evolving digital landscape, data-driven companies must continuously innovate to stay ahead. As the volume and complexity of data increases, managing data schemas and APIs becomes a critical factor influencing business agility, reliability, and...
Homonym and Synonym Resolution in Enterprise Glossaries
Imagine a scenario you've likely encountered: you're in a key strategic meeting, and stakeholders from different departments are converging. They start discussing "repairs"—marketing understands it as customer relationship repair, finance thinks warranty expenses, and...
Data Quality Rule Expression Language Design
In the realm of data-driven decision-making, good data quality isn't just advantageous—it's essential. Leaders who rely on analytics to refine strategies, streamline operations, and enhance competitiveness know that even small inaccuracies or anomalies in their data...
Golden Record Management in Multi-Source Environments
In today's hyper-connected digital landscape, enterprises face the inherent complexity of operating with diverse data sources. Whether it's customer records, transactional histories, or operational metrics, data redundancy and discrepancies are typical pitfalls that...
Distributed Metadata Management Architecture
Facing the exponential growth of data today, organizations are challenged to maintain efficient, scalable, and trustworthy metadata systems. Metadata is the orchestrator behind the curtain, empowering critical operations such as data exploration, governance, lineage...
Data Ownership vs. Data Stewardship: Technical Implementation
In today’s data-driven environment, organizations perceive data not just as a byproduct of operations, but increasingly as a strategic asset that fuels innovation and competitive advantage. However, alongside the technical evolution comes an important debate: data...
Data Taxonomy Development for Unstructured Content
In today's rapidly evolving digital landscape, organizations are often inundated with overwhelming volumes of unstructured content. Emails, documents, audio files, videos, and social media data can create clutter rather than clarity. To turn this tremendous data...
Inter-Company Data Sharing Governance Framework
Navigating today's incredibly fast-paced digital ecosystems requires businesses not only to leverage their data effectively but also to strategically share and exchange it with external partners. Whether it's supply chain insights, customer behavioral patterns, market...
Column-Level Encryption for Sensitive Data Fields
In today's fast-paced digital environment, businesses are the stewards of increasingly vast amounts of sensitive information, from financial figures and employee personal records, to confidential client data. With great data comes not only great opportunity, but also...
User-Driven Data Classification Implementation
Imagine meticulously collecting terabytes of data only to discover significant organizational confusion surrounding what it all truly means. In today's competitive landscape, where accurate decisions hinge on speedy data retrieval, understanding the information in...
Data Field Deprecation Signals and Consumer Notification
In today's rapidly evolving technology landscape, outdated data strategies can spell doom for data-driven enterprises. Yet, even more insidious than outdated systems are obsolete data fields that silently threaten analytics accuracy and operational workflows....
Granular Access Log Implementation for Data Usage Auditing
Imagine being able to trace the exact path any user takes through your organization's data platforms—understanding in real-time who accessed specific data, how frequently, and for what purpose. With businesses increasingly relying on data-driven decisions, granular...
Data Element Cross-Reference Registry Implementation
In our increasingly interconnected digital world, the complexity of data integration across various systems is evolving rapidly. Business leaders are navigating intricate data landscapes, facing constant challenges of data fragmentation and inconsistency. Implementing...
Propagating Data Classification Tags Through Transformations
In a modern analytics environment, data doesn't stay stationary—it constantly transforms, integrates, and morphs to deliver strategic insights. However, as data moves and evolves, its classification tags—privacy, sensitivity, compliance, and ownership—must remain...
Enterprise-Wide Data Type Standardization Framework
Data is the lifeblood of the modern enterprise, fueling innovation, strategic decision-making, and competitive advantage. Yet, despite recognizing its value, many organizations grapple with inconsistent, fragmented data types that hamper their analytical capabilities...
Time-Limited Access Control Implementation for Data Assets
In the rapidly evolving digital ecosystem, companies accumulate vast volumes of data that hold immense operational, strategic, and competitive value. However, protecting sensitive information while allowing appropriate access to stakeholders remains a constant...
Thread-of-Trust Documentation in Data Lineage Chains
In today's fast-paced digital landscape, business leaders rely on a rapidly growing volume of data to drive smarter decisions, automate processes, and foster innovation. Yet, this reliance brings forth complexities in guaranteeing data integrity and trustworthiness....
Record-Level Security Based on Data Content
Imagine you're staring into a seemingly endless ocean of data—the pulse of your organization flowing constantly, carrying insights, opportunities, and inevitably, risks. Each row within your database contains valuable information, yet without effective record-level...
Dynamic Data Masking for Role-Based Data Access
Imagine having the ability to seamlessly protect sensitive data elements without disrupting daily business operations. Enterprises today face an ever-evolving landscape of data privacy regulations, compliance mandates, and cybersecurity threats. Traditional methods of...
Cross-Domain Identity Resolution for Entity Consolidation
Imagine piecing together fragments of a puzzle from different boxes, each set designed by a different person, yet each containing sections of the same overall picture. Cross-domain identity resolution is much like this puzzle, where disparate data points from...
Context-Aware Data Usage Policy Enforcement
In today's rapidly evolving data environment, organizations face unprecedented complexities in maintaining compliance, ensuring security, and leveraging insights effectively. Context-aware data usage policy enforcement represents a crucial strategy to navigate these...
Semantic Layer Implementation for Business Terminology
In the modern enterprise landscape, evolving complexity in data and exploding demand for rapid intelligence mean organizations face significant challenges ensuring disciplined semantics in their analytics ecosystem. A semantic layer implementation, structured...
Digital Rights Management for Dataset Distribution
In an increasingly data-driven world, controlling the distribution, access, and usage rights of valuable datasets becomes paramount. Digital Rights Management (DRM) isn't only fundamental for films and music; modern businesses increasingly apply DRM strategies to...
Consent Management Integration with Data Processing
Innovative organizations today are increasingly harnessing data analytics, machine learning, and artificial intelligence to stay ahead of their competition. But unlocking these powerful insights relies critically on not only accurate data collection and intelligent...
Reference Data Version Control and Distribution
In the era of digital business transformation, effective handling of critical reference data is a cornerstone of operational accuracy. Reference data—those master data sets such as codes, standards, or domain-specific lookup tables that change infrequently yet...
Code Tables vs. Domain Tables: Implementation Strategies
Data is the fuel powering innovative business strategies, analytics, and digital transformation initiatives in today's hyper-connected world. Getting data right is more than just accurate analytics or impressive visualizations; it's about structuring data in systems...
Metadata-Driven Access Control Implementation
In today's digital landscape, businesses grapple with increasing complexities in data privacy, security regulations, and the growing imperative for granular access management. Luckily, there's an intelligent solution at the intersection of data analytics and security...
Attribute Registry Design for Enterprise Data Elements
Organizations today swim through oceans of data, attempting to translate vast amounts of information into actionable insight. But every meaningful data-driven decision begins with effective data governance, starting specifically with how we manage and catalog our...
Application Data Management vs. Enterprise Data Management
In today's data-driven world, companies face increasing pressure to manage and leverage their data effectively. However, not all data management systems are created equal. If you're a decision-maker navigating the nuanced differences between application-specific and...
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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