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TRUSTED BY TEAMS AT
Dev3lop is the right choice for a company of any size.
His easy-going attitude made it very enjoyable to work along.
Our Approach
Empowering data-driven teams,
with relevant expertise.
We empower teams to tackle challenges with skilled local consultants, proprietary tech, and proven methodologies—always prioritizing client success. We help companies leverage programming languages to build innovative solutions, including SaaS app development, without being confined to just SaaS (because that’s far too predictable).
As forward-thinking statisticians, full-stack engineers, designers, and data scientists, we dedicate our time to envisioning the future. Our expertise in emerging technologies has made us a trusted resource for clients seeking insights into what’s next in both front-end and back-end frameworks.
DEV3LOPCOM, LLC has a proven track record of delivering end-to-end, production-grade solutions. We help companies unlock the value of archived data to predict better, optimize, and improve their future. We love what we do.
Internal Slack Messages
The team values communication.
Dashboards in Production
We are data focused, from idea to production.
Dev3lop Team Size
Let us focus on meeting your deadlines.
*estimations are based on custom web crawlers; 35.5k LinkedIn Jobs, 776 career pages, and DEV3LOP data.
Save money hiring fractional software consultants in the USA.
With DEV3LOP, you get direct access to top-tier software consultants at a fraction of the cost hiring full-time in the USA. No middleman or delay.
Save money hiring fractional software engineering consultants in the USA.
With DEV3LOP, you get direct access to top-tier software consultants at a fraction of the cost hiring full-time in the USA. No middleman or delay.
*estimations are based on custom web crawlers; 35.5k LinkedIn Jobs, 776 career pages, and DEV3LOP data.
Our Team
Software Managers focused on solving problems.
Isabelle
Managing Director
Ex: Rolex
Tyler
Software Engineer
Ex: Tableau, PepsiCo
Cody
full-stack engineering
Antoine
board
DEV3LOPCOM, LLC
Boutique Software Consulting Services, based in Austin, Texas! We have created Tableau and Power BI Dashboards, managed projects, and custom data engineering solutions for the following clients.
- The Nielsen Company – 2016 to 2018
- ExxonMobil – 2018 to 2019
- Lever.co – 2020 to 2022
- Colgate, Starkist – 2021 to 2023
- University of Texas, KPRS, Vayda- 2022-2024
Articles.
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...
Backpressure Handling Strategies in Data Streaming Architectures
In today's data-driven ecosystem, timely and continuous data processing has become paramount for businesses aiming to achieve real-time analytics and insights. However, with vast and complex streams of information constantly flowing from numerous sources, managing...
Dynamic Window Computation Models for Real-Time Aggregation
Imagine that your business operates in an environment demanding constant responsiveness. Every second counts—transactions, user interactions, sensor data, or even social media insights flood into your systems continuously. To leverage this torrent of information, you...
Embeddings-as-a-Service: Building a Reusable Semantic Layer
In today's data-driven world, organizations continuously strive to understand their data better and extract meaningful insights quickly. The emergence of sophisticated AI techniques, particularly in natural language processing and semantic understanding, empowers...
Content-Addressable Storage for Immutable Data Warehousing
Imagine your data warehouse as a sophisticated library—a place where performance, accuracy, and scalability are paramount. Now, picture traditional warehousing methods as librarians endlessly reshuffling books, changing their locations, and often losing valuable...
Transductive Transfer Learning for Data Classification with Limited Labels
In the rapidly evolving landscape of data analytics and business intelligence, organizations often face the daunting challenge of classifying data amidst limited labeled examples. When datasets are vast yet labeled data remains scarce, traditional machine learning...
Bloom Filter Applications for Data Pipeline Optimization
In today's fiercely competitive data-driven landscape, businesses are continuously seeking innovative ways to enhance efficiency, reduce latency, and maximize accuracy within their data pipelines. As data strategy evolves towards ever-greater complexity, organizations...
Fuzzy Entity Resolution Techniques for Master Data Management
Master Data Management (MDM) has become a critical cornerstone of organizations aiming to harness their data's true potential. However, the complexity of data sources, varied naming conventions, and inaccuracies make MDM challenging, particularly when standard...
Approximate Query Processing for Interactive Data Exploration
In today's fast-paced analytics landscape, instantaneous insights have become a strategic advantage. As data volumes continue to explode, decision-makers seek interactive data exploration tools that provide real-time feedback. However, traditional query processing...
Ontology-Driven Data Integration: Semantic Approaches to Data Unification
In today's hyper-connected technology ecosystem, every enterprise faces a seemingly endless wave of data. But turning disparate data silos into unified knowledge assets remains elusive. Enter ontology-driven data integration. By establishing semantic frameworks to...
Adversarial Robustness in Automated Data Analysis
In today's competitive technology landscape, organizations increasingly rely on automated data analysis to drive strategic insights, enhance efficiency, and maintain market leadership. Yet, alongside its extraordinary potential lies a significant risk—adversarial...
Hyperloglog Counters for Efficient Cardinality Estimation
In a world driven by massive volumes of data, quick and accurate estimation of unique items is a crucial capability for effective analytics and scalable decision-making processes. Leaders navigating through modern business intelligence and analytics challenges often...
The Impact of AI on Data Engineering Workflows
Artificial intelligence (AI) is more than just a buzzword or emerging trend—it's a strategic imperative reshaping every facet of the data engineering discipline. As data ecosystems become increasingly complex and interconnected, traditional manual processes simply...
Out-of-Order Event Processing Strategies for Reliable Analytics
In the competitive landscape of data-driven enterprises, real-time analytics is increasingly becoming vital. Yet, the rapid influx of event data often arrives out-of-order, posing a significant challenge to organizations striving for timely and accurate insights....
Hierarchical Temporal Memory for Anomaly Detection in Time Series
In a rapidly-shifting digital landscape, staying ahead means mastering complex information streams—and few areas are as demanding as anomaly detection in time series data. As leaders and decision-makers steering enterprises through digital transformation, your success...
Metric Drift Detection: Statistical Methods for Monitoring Data Health
In today's fast-paced data-centric world, organizations increasingly rely on powerful analytics and machine learning models to make timely, intelligent decisions. However, there's an essential factor that can deteriorate performance silently: metric drift. When...
Temporal Tables Implementation: Querying Data Through Time
In today's fast-paced data-centric world, businesses continuously strive for more precise insights that support smarter decision-making and forecasting abilities. Achieving a clear understanding of how data changes over time has become paramount for strategic...
Isomorphic Data Processing: Sharing Logic Between Client and Server
Imagine an environment where your web application seamlessly shares logic between client and server, removing redundancy and slashing development times. Welcome to the innovative world of isomorphic data processing, a strategy reshaping software architecture for...
Cross-Modal Data Alignment Techniques for Unified Analysis
In today's fast-paced data-driven landscape, businesses find themselves managing increasingly diverse datasets—from visual images and textual documents to complex sensor arrays and audio recordings. Understanding and extracting valuable insights require innovative...
Polymorphic Schema Handling in Data Lake Environments
Imagine standing before an expansive, pristine lake—serene yet dynamic, reflecting changing skies overhead. Like the water in this lake, your organizational data doesn't remain static; it continuously transforms, evolving into new forms and complexities. This...
Recursive Materialized View Patterns for Efficient Analytics Hierarchies
As businesses scale and data complexities multiply, your organization's analytics hierarchies can either empower streamlined decision-making or hinder agility with slow and disconnected data. At its core, data analytics success hinges heavily upon how efficiently...
Semantic Layer Optimization for Multi-Dimensional Analysis
Organizations today drown in data but thirst for actionable insights. Effective data management strategies hinge on your ability to transform intricate data landscapes into clear-cut vistas of informed analytics. A sophisticated semantic layer is your bridge from raw...
Asynchronous ETL Choreography: Beyond Traditional Data Pipelines
The traditional Extract, Transform, Load (ETL) data pipelines have served businesses well over many years, yet as organizations face larger data volumes, increasing complexity, and evolving business demands, it's clear that the old-school ETL approach has its limits....
Vectorized Query Processing: Accelerating Your Data Workloads
In today's data-driven business environment, efficiency means the difference between industry leaders setting the pace and those left behind. Executives, strategists, and technical experts alike require rapid insight into vast volumes of data—you simply can't afford...
Feature Store Architectures: The Missing Piece in ML Operations
Picture your organization as a high-performing sports team preparing for a decisive championship game. You've invested in top talent—data scientists, ML engineers, and analysts—yet your crucial plays keep fumbling at key moments. You're producing groundbreaking...
Change Data Capture Topologies for Event-Driven Analytics
In the evolving digital landscape, the immediacy, accuracy, and comprehensiveness of data have become vital ingredients of successful decision-making strategies. As businesses strive to keep pace with rapid innovation cycles and real-time customer expectations, the...
Graph-Based Data Lineage Visualization: Tracing Information Flow
In the rapidly evolving landscape of data analytics and business intelligence, understanding how your data travels through various systems and transformations has become mission-critical. Graph-based data lineage visualization empowers you to trace data from its...
Analytical Sandboxes vs. Production Warehouses: Establishing Boundaries
In the realm of modern data strategy, discerning between exploratory analytical environments (sandboxes) and secure, established production data warehouses is crucial for every data-driven business. Decision-makers often grapple with blurred distinctions, which...
Ephemeral Computing for Burst Analytics Workloads
Bursting analytics workloads—characterized by short-lived, highly intensive computing demands—have become ubiquitous in data-rich environments. Enterprises tackling such fluctuating data workloads require a computing strategy that's agile, scalable, and economically...
Query Mesh Optimization: Routing Data Operations for Performance
As organizations grow, the complexity and diversity of data operations quickly escalate. It's no longer viable to rely solely on traditional query acceleration techniques or singular database implementations—modern organizations need strategic query routing that...
A Practical Guide to Dimensional Modeling
In today's data-driven world, almost every strategic decision hinges upon insightful, accessible, and actionable information. Businesses generate massive volumes of data daily, yet without sound techniques for structuring and analyzing this data, it remains untapped...
DataContract-Driven Development: Aligning Teams Around Data
Enterprises increasingly rely on a tangled web of APIs, platforms, and microservices, ensuring consistency, quality, and clarity is becoming critical. DataContract-driven development is the forward-thinking approach that cuts through complexity—aligning development,...
Idempotent Data Transformations: Ensuring Consistency During Reprocessing
The first time I read the word idempotent, I needed to read it a few times. It's pronounced; /ˌīdemˈpōtnt,ˌēdemˈpōtnt/ -- like, eye-dem-potent. It helps if you say this out loud a few times. The accuracy of analytics pipelines can significantly impact your bottom...
Hyperdimensional Computing Approaches to Analytics
Businesses confront immense volumes of complex and multi-dimensional data that traditional analytics tools sometimes struggle to fully harness. Enter hyperdimensional computing (HDC), a fresh paradigm offering breakthroughs in computation and pattern recognition. At...
Immutable Data Architectures: Benefits and Implementation Patterns
In today's fast-moving landscape of data innovation, harnessing the power of your organization's information assets has never been more crucial. As companies ramp up their analytical capabilities, decision-makers are grappling with how to ensure their data...
Edge Analytics Mesh: Processing Data Where It’s Generated
Imagine a world where information is transformed seamlessly into actionable insights at the exact point where it originates. No waiting, no latency, no unnecessary routing back and forth across countless data centers—only real-time analytics directly at the data...
Creating Accessible Data Visualizations for All Users
In today's data-driven world, compelling visual storytelling is not just an added value— it's a necessity. The challenge many organizations face, however, is ensuring their data visualizations don't just captivate audiences—they also remain accessible and meaningful...
The Role of Data Engineers in the Age of AI
In today's rapidly evolving technological landscape, artificial intelligence (AI) has transitioned from futuristic buzzword to critical business advantage. As organizations race to leverage AI for predictive analytics, automation, decision-making, and innovation, the...
Hexagonal Architecture for Data Platforms: Ports and Adapters
Data has transformed into the lifeline of organizations seeking to maintain technological leadership and innovation. Yet, as data platforms grow increasingly complex, engineers and strategic decision-makers continually face challenges around system modularity,...
Polyrepo vs. Monorepo Strategies for Data Platform Code Management
When it comes to managing modern data platforms, choosing the right repository structure is a decision that can significantly impact your team's productivity, collaboration, and overall success. As data-driven innovation accelerates at an unprecedented pace, your...
Zero-Copy Integrations: Minimizing Data Movement Costs
Data is the lifeblood of the modern enterprise, but moving data around carelessly can become costly and inefficient. Businesses that understand the importance of streamlining data management embrace zero-copy integrations as a core strategy. Imagine organizations...
Golden Signals for Data Pipelines: What to Monitor and Why
In today's data-driven landscape, reliable data pipelines form the backbone of success for any enterprise keen on innovation and analytics. As organizations collect, process, and leverage an unprecedented amount of data, monitoring the health and performance of these...
Operationalizing Data Skew Detection in Distributed Processing
In today's analytics-driven landscape, making informed business decisions depends heavily on timely and accurate data processing. Organizations across industries rely on distributed processing frameworks to handle the growing volumes of data. However, one issue that...
Schema Evolution Patterns with Backward/Forward Compatibility
In today's fast-paced digital ecosystem, data has undeniably become the lifeblood of successful enterprises. Organizations, driving innovation across industries, now face a crucial challenge — managing the evolution of their data schemas to sustain agility, maintain...
Entropy-Based Data Quality Monitoring: Detecting Anomalies Early
Every innovative enterprise understands that in the modern business landscape, data is no longer just an asset—it’s a strategic weapon. High-quality data fuels precise decision-making, accurate forecasting, and reliable insights. On the flip side, poor data quality,...
Domain-Driven Data Design: Bounded Contexts in Data Platforms
In an era where organizations increasingly rely on data-driven insights to fuel growth and innovation, managing complexity has become a significant challenge. Ineffective data management strands organizations in complexity silos, inefficiencies, and misalignment....
Declarative Data Transformation: Moving Beyond Imperative Scripts
In today's fast-paced, innovation-driven data environment, many organizations still find themselves stuck using traditional imperative methods for data transformation tasks. Imperative scripts might seem straightforward initially—like a recipe listing each ingredient...
Holographic Data Modeling for Multi-Perspective Analytics
In today's rapidly evolving data landscape, conventional data modeling techniques are no longer sufficient for organizations seeking real-time insights and diverse analytical perspectives. Decision-makers need a comprehensive view of their business that accounts for...
Quantum-Resistant Encryption for Sensitive Data Storage
In an era marked by transformative waves of digital innovation, the rise of quantum computing looms as both a groundbreaking advancement in technology and a critical security concern. Quantum computers possess an unprecedented ability to harness quantum...
Computational Storage: When Processing at the Storage Layer Makes Sense
In today's data-driven era, every business decision hinges on immediate, accurate, and insightful information. Companies face an escalating avalanche of data, and traditional methods of processing data as an afterthought fall short when performance, scalability, and...