Our Data Engineering professionals can assist you with using the data you collect and developing innovative data pipelines utilizing cutting-edge technologies and platforms.
We are experienced in both Cloud technologies and on-premises solutions. We have hands-on expertise with AWS, GCP, and Azure data engineering.
– Nael QAWAS, Chief Technology Officer at AI Bigdata Solutions
What is Data Engineering?
Data engineering is the practice of designing and building systems for data collection, storage, and analysis. This is an extensive field of application in almost all industries. Data engineering includes many data science majors.
In addition to providing access to data, data engineers create an analysis of raw data to provide predictive models and show short-and long-term trends.
Without data engineering, it would be difficult to make sense of the huge amounts of data available to companies.
Who is a Data Engineer?
Data engineers are familiar with a variety of programming languages used in data science. Data engineers build data pipelines that connect data from one system to another.
They are also in charge of transforming data from one format to another, allowing the data scientist to obtain data from other systems for analysis.
What Is Data Engineering Services?
The Addepto Data engineering services will help your business in advancing to the next level of data usage, data management, and data automation.
Our specialist team assists worldwide enterprises such as JABIL, SITA, and J2 Global in the development of data processing pipelines.
We are working with our customers to extract important business information, manage data, and ensure the highest level of data quality and availability.
Our project strategy and data engineering services were created to help companies make better decisions. You may focus on insight extraction thanks to automated advanced data pipelines.
AI Bigdata Solutions team is at your service!
During our 3+ years on the market, we have delivered 100+ projects for 30+ clients in different industries.
We approach every customer very individually and determine a specific project approach.
We cooperate to define technologies, infrastructure, and advanced technologies that will solve specific business challenges and match your architecture.
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.
AI Bigdata Solutions 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
AI Bigdata Solutions 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.
1. Understanding business needs and technical requirements
Firstly, our data engineering team carries out the workshops and discovery calls with potential end-users. Then, we get all the necessary information from the technical departments.
2. Analysis of existing and future data sources
At this stage, it is essential to go through current data sources to maximize the value of data. You should identify multiple data sources from which structured and unstructured data may be collected. During this step, our experts will prioritize and assess them.
3. Building and implementing a Data Lake
Data Lakes are the most cost-effective alternatives for storing data. A data lake is a data repository system that stores raw and processed structured and unstructured data files. A system like stores flat, source, transformed, or raw files.
Data Lakes could be established or accessed using specific tools such as Hadoop, S3, GCS, or Azure Data Lake on-premises or in the cloud.
After selecting data sources and storage, it is time to begin developing data processing jobs.
These are the most critical activities in the data pipeline because they turn data into relevant information and generate unified data models.
The next step is one of the most important parts in data development consulting – DevOps. Our team develops the right DevOps strategy to deploy and automate the data pipeline.
This strategy plays an important role as it helps to save a lot of time spent, as well as take care of the management and deployment of the pipeline.
Testing, measuring, and learning — are important at the last stage of the Data Engineering Consulting Process. DevOps automation is vital at this moment.
The AI Bigdata Solutions 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.
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.
High quality
You don’t have to worry about the quality thanks to our expertise
Increased efficiency
We implement solutions that can save you thousands of dollars in operational costs
Start in 1 week
We can assign experts to your project in as short as 1 week
Savings
Creating own AI departments might be a big investment for the future
Finished Projects
Experienced Data Science engineers
In savings for all our customers
Average ROI from the project
Satisfied Clients
Case Study I
We’ve helped a leading manufacturing company enhance management efficiency by implementing an automated reporting and demand prediction system, with predictive maintenance capabilities.
Solution: Our AI consultants have developed and created a system that helps managers and operation leaders to make the right decision on the costs and demand planning. Predictive maintenance solution is predicting when a particular production machine needs to be checked and potentially replaced.
Benefits: one integrated data platform. Yearly savings of around 10m $ on right demand planning and inventory management. Continues production process and prevention from machine failures which are resulting in millions of dollars.
Case Study II
We’ve helped one of the global retail & e-commerce companies to optimize advertising processes using AI, ML, and ad targeting. We increased the effectiveness of the operational activities using image recognition.
Solution: Using advanced AI technologies our consultants created algorithms that help to find the best time to spend, identify the right channels and slots, and automate bidding for ad space. Image recognition and computer vision technologies were used for planogram execution, signing detection, and inventory automation using shelf analysis.
Benefits: 60 hours of labor saved each month. 30% advertising cost decrease and improving conversion rate by 5 p.p (from 16% to 21%) that led to the sales increase in around hundred of thousand dollars.
Tools and frameworks for AI solutions
Python – one of the main technologies for AI today. Used for building and creating algorithms, data pipelines, advanced functions and statistical models.
PyTorch – is an open-source deep learning framework built to be flexible and modular for research, with the stability and support needed for production deployment.
TensorFlow – is an open-source library for numerical computation. It is mainly used for classification, perception, understanding, discovery, prediction, and creation.
R – The R language is widely used among statisticians and data miners for developing statistical software and data analysis.
Hadoop – is an open-source software framework for storing data and running applications on clusters of commodity hardware. It provides massive storage for any kind of data, enormous processing power, and the ability to handle virtually limitless concurrent tasks or jobs.
MongoDB – a document-oriented database that stores data in JSON-like documents with the dynamic schema. It is great for transactional stores where performance is a concern. Its schema-less operations allow you to update the data on the fly.
PySpark – used to transform data. It enables you to run AI applications on billions of data on distributed clusters 100 times faster than the traditional python applications.
What AI consulting services can you expect?
AI Bigdata Solutions may offer to you a variety of AI services, starting from an AI strategy roadmap to building a scalable AI infrastructure and production-grade AI solution deployment.
AI Strategy Roadmap – validate feasibility of using AI in your company, analysis of available data and data monetization potential
AI proof-of-concept projects – test assumptions and hypotheses. We are delivering fast and reliable MVP solutions in 4-6 weeks.
Production grade AI implementation – implementing algorithms and models to support your business’s production systems and deliver insights in real-time
Support – we help our customers in model validation, quality control and system stability
Post-implementation warranty – we guarantee that our AI algorithms will bring you value and high accuracy
What does an AI consultant do?
The role of an AI consultant is complex. AI consulting includes many tasks faced by data scientists and more. AI consultants need to help in creating an overall system based on different requirements necessary for successful implementation.
Moreover, they are responsible for managing AI-driven projects as well as are considered experts by DevOps teams who support them in capacity building making sure that internal resources are supporting code and artificial intelligence infrastructure.
At AI BigData Solutions, our AI consultants stay in touch on a daily basis with our clients. This way you can be sure that your project is our top priority.
Our AI experts will help you to:
- solve complex business challenges using analytic algorithms and AI
- design, build and deploy predictive and prescriptive models using statistical modeling and optimization
- use structured decision-making to complete projects
- manage an entire AI project from business issue identification, data audit to model maintenance in production.
Our partners & AI consulting review
“AI BigData Solutions offered an individual approach to our needs and high-tech solutions that will be efficient in the long term. They conducted detailed analysis and were open to trying out innovative ideas.”
“AI BigData Solutions has an individual approach from the very beginning. They are open to change and ready to face difficulties.”
““What I find most impressive about AI BigData Solutions is their individual approach and effective communication. Their ability to create custom analytics solutions was impressive.”