Data Engineering Services
Data lake and data warehouse
Altoros assists you in storing structured, semi-structured, unstructured, and binary data aggregated from disparate sources. With current and historical data gathered in a single point, you get a consolidated view of your business processes.
Altoros ensures smooth migration of massive data arrays to cloud storages without data loss or downtime. We launch new suitable infrastructures, as well as prepare and optimize data for migration, while taking care of security.
Continuous integration and deployment
Hire a team of certified experts to enable smooth integration of custom apps with third-party systems and aggregate data from multiple sources for further analysis. At Altoros, we integrate disparate data sources by implementing the ETL pipelines. Our engineers and consultants help you to maintain consistency of data landscape, as well as guarantee an error-free data flow.
Data analytics and visualization
Develop data management solutions to visualize and analyze data for informed decision-making. Increase the visibility of business processes, automate reporting, and get valuable data insights in real time.
Data storage and ETL processing
We perform data extraction, cleansing, profiling, normalization, and transformation. Our team also enables data processing, mining, and warehousing. We will help you to design ETL pipelines based on Hadoop HDFS, Amazon S3, GCP Cloud Storage, Azure Blob Sore, and the DSE distributed file system.
Data pipeline development and implementation
Our experienced data engineers build and implement scalable data pipelines for businesses across various industries. We make sure your data flows are designed properly, so that you can stay focused on business-critical tasks.
What you get
Our team comprises over 10 data engineers and data scientists who have in-depth expertise in aggregating, analyzing, and transforming data for your particular needs.
Pattern definition. Define hidden opportunities by transforming raw unstructured data into meaningful insights.
Predictive modeling. Forecast market trends and predict the outcomes of various scenarios to increase revenue while minimizing risks.
Risk assessment. Early identify and prioritize potential risks to make timely adjust your business strategy.
Fraud detection. Employ a variety of big data processing tools and algorithms to detect fraudulent activities.
Recommendation engines. Develop self-learning engines to increase sales conversion rate by enabling personalized recommendations.
We are contributing
Altoros has extensive experience in employing NoSQL databases:
Data store development, integration with other technologies, and performance fine-tuning.
Our engineers developed the NuoDB Migrator that enables users of traditional SQL databases to easily migrate their data to NuoDB.
Altoros contributed to the development of Couchbase Server and regularly performs independent evaluations of the database as it evolves.
Altoros benchmarked a number of Redis-based products: Redis Enterprise Cloud, ElastiCache, openredis, RedisGreen, and Redis To Go.
Why is data engineering important for your business?
A data-driven approach allows to proactively address business-critical issues and bring value. Companies implement robust database management systems to speed up and automate data analysis and processing, which enables them to predict short-/long-term customer trends efficiently.
When you turn to such data engineering service providers as Altoros, you may be confident that data engineers will help with the development and implementation of high-load distributed systems tailored to your business needs.
1400+ projects delivered in 30+ countries. We develop custom software solutions to automate business workflows, facilitate data management, and power data-driven decisions. Check out our featured big data and data engineering projects.
The NuoDB Migrator for Moving SQL Data to a NoSQL Database
NuoDB is a NewSQL database platform with a unique geo-distributed database management system. It provides linear scalability, outstanding scale-out performance, continuous availability and can run anywhere—in a local data center, in multiple data centers around the world, or in the cloud. With support for multiple platforms, users are able to build hybrid solutions that have both Linux and Windows hosts.
Highly Scalable System for DNA Analysis
The customer turned to Altoros to improve its biotechnology system that analyzes DNA samples for mutations on early stages. The legacy tool was able to de-duplicate only 1,000 samples maximum—due to memory and CPU limitations—and it still took hours (or even days) to process the pipeline. The goal was to fix performance bottlenecks as well as enable linear scalability for processing 10,000+ bio samples at a time.
The Image Recognition System
The system is an innovative augmented reality application that recognizes visual objects and enables consumers to find information about what they see on a TV screen, billboards, or anywhere else right in the moment. Users can simply scan an image and the system will provide all the information about advertised goods or services.
Enabling Digital Identity Authentication and Verification
A global provider of digital identity and anti-fraud solutions turned to Altoros to enable identity verification, electronic signatures, and secure agreement automation.
The Cloud-based Document Exchange System
Normally, e-mail service providers limit the size of data sets that can be sent at a time. In addition, users have to employ third-party software to create documents with complex structures, multiple elds, diagrams, and tables. The customer is a provider of advanced document exchange services who designed software that eliminates these drawbacks.
The SNP Detection System
The customer helps scientists and laboratories to conduct research and experiments in the field of life sciences. Their key services include next-generation sequencing, bioanalytical and mass spectrometry, as well as DNA sequencing. The customer turned to Altoros to develop a solution that would detect SNP in digitized DNA sequences saved in the FASTA/FASTQ format easier and less time-consuming.
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