Data Science
We are a leading Data Science and AI consulting company, dedicated to creating cutting-edge AI-driven services that unlock the true potential of your accumulated data. Our expertise in data science and artificial intelligence empowers your company to maximize the value derived from your data assets.
Business benefits
Data Engineering Services
Data Science Consulting Services
- Discover the diverse range of Data Science consulting services offered by Datable.
- Experience the unique benefits that implementing AI solutions can bring to your business.
- Explore how Artificial Intelligence is revolutionizing various industries, including retail, eCommerce, manufacturing, finance, healthcare, marketing, and gaming.
Technologies
- Our expert team develops tailor-made AI solutions using cutting-edge technologies.
- We leverage advanced techniques such as Computer Vision, Natural Language Processing, Predictive Analytics, Image Recognition, Recommendation Engines, Smart Search Engines, and more.
Benefits
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- Embrace the self-learning capabilities and scalability of AI for your business advantage.
- Leverage AI algorithms to cater to thousands of customers through SaaS applications.
- Tap into the potential of AI's personalized recommendation systems, enhancing your marketplace offerings.
- Join the majority of leading businesses that invest in AI for a competitive edge.
Our Team
- Our dedicated data scientists maintain daily communication with our clients, ensuring your project is a top priority.
- Benefit from our data science and AI experts' proficiency in solving complex business challenges with analytic algorithms.
- Rely on us to design, build, and deploy predictive and prescriptive models using statistical modeling and optimization.
- Trust our structured decision-making approach to deliver successful projects from issue identification to model maintenance in production.
Development process
Our process
Product Traceability System for a big manufacturing company
We helped JABIL a big electronic manufacturing company to build a complex Data Lake system based on AWS for Product Traceability.
Addepto Data Architects and data engineering experts have designed and implemented an end-to-end scalable system for fast analytical reporting and data storage.
Customer Data Platform implementation
Addepto team has supported the Custimy team with their data lake and analytics journey.
Our data engineering team has created a tailor-made data transformation layer for both structured data and Digital Marketing data sources, combined together in a single and unified cloud data warehouse.
- Manufacturing
- Retail
Technologies
Our Data Engineering Tools and Technologies
The Addepto team uses the most advanced tools and technology on the market. To supply stable and high-quality software, we partner with the largest cloud solution providers (AWS, Azure, and GCP). Our data engineering team is also deeply committed to the open-source community and technology, so our clients don’t have to pay extra for some of the most popular data engineering software.
- Frameworks
- Software
MLflow – MLflow is an open-source platform to manage the complete machine learning lifecycle, including experimentation, reproducibility, deployment, and a central model registry.
Kedro – Kedro is an open-source Python framework for creating reusable, maintainable, and modular data science code.
Apache Airflow – Apache Airflow is an open-source tool to programmatically create, schedule, and monitor workflows, used by Data Engineers for orchestrating workflows or pipelines. It enables them can easily visualize their data pipelines' dependencies, progresses, code, tasks, and success status.
Apache Spark – Apache Spark is a data processing framework that can quickly perform tasks on large data sets. It can work alone but also distribute data processing across multiple computers.
Amazon Sagemaker – Amazon SageMaker is a machine learning service that enables data scientists and developers to speed up building and training machine learning models and directly deploy them into a production-ready hosted environment.
Kubeflow – Kubeflow is the open source machine learning toolkit on top of Kubernetes. It provides the cloud-native interface for your ML libraries, frameworks, pipelines and notebooks, interpreting stages in the created data science workflow into Kubernetes steps.
AutoKeras – AutoKeras is an open-source python package written in the deep learning library Keras. AutoKeras uses a variant of ENAS, an efficient and most recent version of Neural Architecture Search.
Key benefits
Ways that Data Science can improve your business
Glossary
FAQ
How big tech companies use data engineering?
Many e-commerce giants use the power of data to create value for their businesses. Specific data allows you to attract potential customers and thereby significantly increase business profits.
Amazon personalizes every interaction by using a large amount of client data.
Data is being used by the company to optimize pricing, advertising, the supply chain, and even to decrease fraud.
Nordstrom’s data engineers have developed a system for monitoring customer habits and behavior using Wi-Fi.
The data obtained allowed the company to study the purchasing trends of its customers, which resulted in the optimization of personalized data and overall improved customer service.
What is the difference between Data Engineering and Data Science?
Data science is an interdisciplinary field that uses methods and techniques from statistics, applied science, and computer science to analyze organized and unstructured data to provide useful insights and information.
Data engineering is responsible for creating a pipeline or procedure to transport data from one instance to another.
Do I need Data Engineering?
We are surrounded by data. This resource may be used for a variety of purposes, including customer service, market research, and, of course, sales. Developing sophisticated data systems for businesses is quickly becoming necessary.
You should hire data engineering consulting experts to organize your system and use the data to improve your business performance.
What is a Data Pipeline?
A data pipeline is a sequence of data processes that extract, process, and load data from one system to another.
Data pipelines are classified into two types: batch and real-time.
What is the future of Data Engineering?
The following four areas were highlighted as technological shifts in data engineering of the future:
- Increased connectivity between data sources and the data warehouse.
- Self-service analytics with intelligent tools made possible by data engineering
- Automation of Data Science functions
- Hybrid data architectures spanning on-premises and cloud environments
What does a Data Engineer do?
Data engineers are responsible for the design, development, and maintenance of the data platform, which includes the data infrastructure, data processing applications, data storage, and data pipelines.
In a large company, data engineers are usually divided into teams that focus on different parts of the data platform: Data warehouse & pipelines, Data infrastructure, Data applications.
Why is Data Engineering so important?
To establish a genuinely effective analytics program, companies must intentionally invest in developing their data engineering expertise.
This includes building a solid basis for data management-identifying gaps and quality concerns while improving data collecting.
Companies that actively invest in engineering professionals will get the most out of data in the coming years.
Check out our blog and make sure you are keeping up with the last trends in your industry
Data Science vs. Data Engineering
What are the main tools and programming languages used in data engineering and data science?
Find out the main difference between these two fields.
Who is a Data Engineer?
The profession of Data Engineer was ranked as the fastest-growing tech job in 2019!
With the number of open positions up 50% compared to last year.
Data Lake Architecture
In this article, you can learn more about Data Lake Architecture.
Learn what are the key factors you should keep in mind when planning Data Lake Architecture.
We are a fast-growing company with the trust of international corporations
Addepto on the list of top 10 AI consulting companies by Forbes.
We are proud to be among the top BI & Big Data Consultants in Los Angeles on Clutch
We are proud to be among the top BI & Big Data Consultants in Los Angeles on Clutch
We are proud to be among the top BI & Big Data Consultants in Los Angeles on Clutch
We are proud to be among the top BI & Big Data Consultants in Los Angeles on Clutch
Our clients
Let's discuss
a solution
for you
Edwin Lisowski
will help you estimate
your project.
- hi@addepto.com
Addepto offered an individual approach to our needs and high-tech solutions that will be efficient in the long term. They conducted a detailed analysis and were open to trying out innovative ideas.
Przemysław Piekarz Sales Analysis Manager – InPost