Big Data
Highlights about naztech big data services
Our big data services help businesses make data driven decisions by unlocking valuable insights.
- During last six years in data analytics and data science, we have been satisfying companies’ diverse analytical needs. Such as the need for advanced analytics, which makes us fully understand the digital transformation.
- We hold partnerships with big data service providers to keep pace with the technological advancements and the evolution of the data analytics landscape.
- We have successful intelligent system implementation applying the Data Analytics and Data Platform.
- We strive to assure the quality of the big data consulting services and the security of the customers’ data.
Talk to our experts today!
Dimension of our Big Data Services
We partner with big data technology service providers and assist businesses
where they are in their journey to extract value from data and turn them into actionable insights. We unlocking competitive advantages for organizations
Data Ingestion
Data Ingestion
We connect multiple sources of data and our capabilities help discover potential sources of data and build a robust Data Ingestion mechanism to collect, ingest, and manage multiple data sources.
Data Pipeline
Data Pipeline
To manage volume, variety, and velocity of data, our experienced data engineering teams build Data Pipelines that have integrated quality checks to process stream (real-time) or batch (historical) data.
Artificial Intelligence
Artificial Intelligence
Our Artificial Intelligence capability integration make your business to build custom models to automate decision making. Thus help you to build intelligent systems and intelligent office.
Data Storage
Data Storage
Our Data Storage experience includes engineering scalable data warehouses and data lakes to efficiently store and retrieve data. We emphasizes on the Proficiency in databases, multiple tech stacks, and database models such as Graph, Search, Columnar, and Time series ensure that we choose the best available solution to suit business use case to make data available fast and in the right format.
Business Intelligence & Analytics
Business Intelligence & Analytics
Business Intelligence also leverages our Analytics capabilities to build interactive and self-service dashboards to consume and visualize their data to derive insights for enhanced decision making. We leverage your BI platforms and systems to suit the business needs.
Big Data Consulting
- Big data implementation strategies and detailed evolution roadmaps.
- Recommendations on data quality management.
- Big data solution architecture + an outline of an optimal technology stack.
- User adoption strategies.
- A proof of concept (for complex projects).
Our big data implementation process:
- Analyzing big data.
- Designing big data solution architecture.
- Developing big data solution
- Setup of big data governance procedures (big data quality, security, etc.)
- ML models development.
We also provide big data managed analytics services.
Big Data Solutions
Big Data Solutions Steps:
- Create Data Lake,
- Store data in Data Ware House
- Process Data Mining
- ETL/ELT setup
- Data analysis (SQL and NoSQL)
- Big data reporting and dash boarding
We offer:
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- Big data analytics solution.
- Big data solution infrastructure setup and support.
- Big data extraction and management.
- ML model development and tuning.
- Predefined and ad hoc reports (within several weeks after our cooperation starts).
Our Big Data Analytics
Use Cases
Talent Array
Data Mining
- Collecting, processing and storing large volumes of job related data from multiple jobsites. (Job offering data, opening new job, job categorization, plans, etc.
- Detecting deviations and undesirable patterns in a job trend
- Recognizing job sources such as job categories, resource availability, etc.
- Conducting cause-effect analysis.
- Forecasting analysis demand, capacity, archiving job resources.
- Job category and operational risk management.
Docutech
Big data warehousing
- Storing operational data about business processes, finances, resources, customers, etc.
- Analytical querying and reporting on archived documents.
- Revenue, cost and investment analytics.
- Performance analytics dashboard.
- Predicting, archiving, planning for performance measure
