Data Engineering
Data collection, creation of pipelines and data architects, ETL and their literacy – all this is assigned to Data Engineering. Amazinum specialists create a data product qualitatively and professionally
Data collection, creation of pipelines and data architects, ETL and their literacy – all this is assigned to Data Engineering. Amazinum specialists create a data product qualitatively and professionally
What is Data Engineering
Data Sets
Classification
Database
Statistics
Pre-processing
Analytics
Evaluation
Zippia research predicts that the data engineering job market will grow by 21% between 2018 and 2028.
Fior Markets reports that the global market for big data and data processing services is expected to grow from USD 32.45 billion in 2017 to USD 123.89 billion by 2025 at a CAGR of 18.2% during the forecast period 2018- 2025 years.
Data Engineering is
the process of data management, which means setting up certain mechanisms for collecting and storing data. This process structures all the data that will be used in the business. In this way, unstructured and messy data is transformed into organized information that can be used by Data Scientists in the future. In this case, the creation of ML models or data analysis directly depends on providing Data Engineering with an organized standard flow. Data can flow across teams and organizations.
Data Sets
Classification
Database
Statistics
Pre-processing
Analytics
Evaluation
Zippia research predicts that the data engineering job market will grow by 21% between 2018 and 2028.
Fior Markets reports that the global market for big data and data processing services is expected to grow from USD 32.45 billion in 2017 to USD 123.89 billion by 2025 at a CAGR of 18.2% during the forecast period 2018- 2025 years.
Data Engineering is
the process of data management, which means setting up certain mechanisms for collecting and storing data. This process structures all the data that will be used in the business. In this way, unstructured and messy data is transformed into organized information that can be used by Data Scientists in the future. In this case, the creation of ML models or data analysis directly depends on providing Data Engineering with an organized standard flow. Data can flow across teams and organizations.
Data Engineering tools
Python
Apache Hadoop
Julia
Relational and Non-relational Databases
Apache Spark
Python
Apache Hadoop
Julia
Relational and Non-relational Databases
Apache Spark
We are experienced in Data Engineering tools:
Structured data can easily be stored in a relational database.
Semi- or unstructured data uses non-relational or NoSQL databases
SQL and NoSQL databases:
- MySQL
- Microsoft SQL Server
- PostgreSQL
- MariaDB
- MongoDB
- Firebase
- Elasticsearch
- Apache Cassandra
- Apache HBase
In-memory data stores
- Redis
- Memcached
- SAP HANA
- SingleStore
- Oracle TimesTen
Storage platforms are often used in big data development
Data warehousing solution:
- Google BigQuery
- Amazon Redshift
- Snowflake
- Vertica
- Azure Synapse Analytics
Workflow planning tools will help improve the data development process.
Automation and scheduling tools:
- Apache Airflow
- Luigi
- Apache Oozie
- Azkaban
Optimize Your Data Infrastructure
Why Do You Need Data Engineering?
Obtaining important information from large data sets, which in conclusion helps to make important decisions after data analysis
Data is directly linked to a wide range of business functions, from finance to sales
Cleaning large disparate data that can answer critical business questions
Preparation of information for further work of analysts, data processing specialists, and managers
High-quality management of business processes, thanks to processing and obtaining information from a large amount of data
Processing large amounts of data without overloading systems allows for scalability
Robustly built and optimized data architecture allows to prevent errors from occurring when working on large amounts of data
Companies with good data engineering practices can use their data to make better decisions and get a leg up on their competitors
Data engineering helps companies organize themselves more efficiently: it can handle as much volume as possible while still being cost-effective
Use cases of Data Engineering
Healthcare
Data engineering in healthcare helps to acquire and integrate large volumes of patient data, such as electronic records (EHR), wearable devices, and medical imaging systems. With pipelines that ensure a seamless flow of data, healthcare providers gain access to patient information. In conclusion, this can improve patient care, provide quality predictive analytics, and aid in medical research.
Fintech
Data engineering helps to collect and consolidate financial data from various sources. Aggregated transaction data, market data, and customer information are carried over data channels. It enables risk modeling, fraud detection, and investment analysis to help financial institutions make informed decisions and comply with regulatory requirements.
Manufacturing and supply chain
Data Engineering will help your business optimize the supply chain by integrating data from sensors, RFID tags, and other sources. Channels can monitor the production process in real-time. This will allow companies to increase efficiency, minimize costs, and improve weak points.
E-commerce and personalization
Support personalized shopping thanks to data engineering. Data Engineers at Amazinum will help you design data feeds and process transaction history data, click data, and customer behavior. This helps you fine-tune your referral mechanisms, which will help you attract customers and increase sales.
Energy and utilities
Our Data Engineers will help you combine data from smart grids, sensors, and renewable energy sources to create reliable data pipelines. They will help you track and manage your energy consumption to optimize energy distribution, reduce your carbon footprint, and help optimize energy development.
Transportation and logistics
Amazinum engineers help you manage complex data streams from GPS trackers, in-vehicle sensors and supply chain partners. Thanks to this, you can optimize route planning, track shipments and take your business to the next level.
Healthcare
Data engineering in healthcare helps to acquire and integrate large volumes of patient data, such as electronic records (EHR), wearable devices, and medical imaging systems. With pipelines that ensure a seamless flow of data, healthcare providers gain access to patient information. In conclusion, this can impro
ve patient care, provide quality
predictive analytics, and aid in medical research.
Fintech
Data engineering helps to collect and consolidate financial data from various sources. Aggregated transaction data, market data, and customer information are carried over data channels. It enables risk
modeling, fraud detection, and investment analysis to help financial institutions make
informed decisions and comply with regulatory requirements.
Manufacturing and supply chain
Data Engineering will help your business optimize the supply chain by integrating data from sensors, RFID tags, and other sources. Channels can monitor the production process in real-time.
This will allow companies to increase efficiency, minimize costs, and improve weak points.
E-commerce and personalization
Support personalized shopping thanks to data engineering. Data Engineers at Amazinum will help you design data feeds and process transaction history data, click data, and customer behavior. This helps you fine-tune your referral
mechanisms, which will help you attract customers and increase sales.
planning, track shipments and take your business to the next level.
This will help farm owners to increase productivity and manage resources efficiently.Agriculture and farming
Data Amazinum engineers will be able to integrate data from sensors, weather stations, and GPS devices to support and optimize agriculture. Conveyors created by our specialists will shed light on optimal sowing times, irrigation needs, and pest control. This will help farm owners to increase productivity and manage resources efficiently.
Explore Our Data Engineering Solutions
Amazinum Portfolio in Data Engineering
Advantages of engaging the Amazinum company
7
Years
We offer you our 7 years of expertise in data science.
40+
ML Engineers
We have a large talent pool of highly-skilled ML engineers of Middle and Senior-level professionals.
16
Active Projects
Our team has successfully connected Machine Learning Engineers to technical departments in more than 19 companies.
Advantages of engaging the Amazinum company
7
Years
We offer you our 7 years of expertise in data science.
40+
ML Engineers
We have a large talent pool of highly-skilled ML engineers of Middle and Senior-level professionals.
16
Active Projects
Our team has successfully connected Machine Learning Engineers to technical departments in more than 19 companies.
We develop unique solutions created for a specific project and client’s requirements.
The Amazinum team takes market features and micro and macro risks in the development of POCs in order to optimize your efforts and resources.
We take care of the qualifications of each specialist we offer for the project. Due to the presence of more than 40 specialists, we select a Data Scientist who has experience in a specific domain with specific technologies.
You may not worry about the employee if the case of termination or suspending of assignment, as well you don’t need to hire the specialist in advance in cases of uncertain project start
Our Industry Focus
Our industry knowledge and background give our clients and partners confidence that we understand their business. Here we highlighted a few top industries we are good at, penetrating to the smallest details and nuances of a certain branch.
SEO & Marketing
Healthcare
Safety & Security
Sport
E-commerce & Retail
Gambling and Casino
Manufacture
Ecology
FinTech
Energy
Localisation
IoT
Vitaliy Fedorovych
CEO, Data Scientist at Amazinum
Hello there!
Amazinum Team assists you through all data science development processes:
from data collection to valuable insights generation.
Get in touch with our CEO and Data Scientist to figure out the next move together
- 4A Peremohy square, Ternopil, Ukraine, 46000
- +380 98 85 86 330
- vfedorovych@amazinum.com
Contact Us
Contact Us
Bazarnitska Alina
Client Partner
Ihor Khreptyk
Client Partner
Stopnyk Zoriana
Client Partner
Vitaliy Fedorovych
CEO, Data Scientist
