Data Platform Services

Data protection, data privacy, and data security have become a major concern for citizens and governments worldwide. Privacy is a must when it comes to designing and has become a legal obligation that varies between each region. As a result, numerous data protection laws such as the GDPR (General Data Protection Regulation) in Europe, the CCPA (California Consumer Protection Act) in North America and PDPA (Personal Data Protection Act) in Singapore have been enacted or are close to being.

Uvionics Tech is here to help you comply with data protection and sovereignty law, data governance, data protection as a practical approach for compliance. Highly experienced in architecting and development of platforms and solution that complies with GDPR, PDPA or CCPA, our expertise in the field helps you design and operationalize data and workflows that control all along your data pipelines with established processes, while all personal data is under your control.

We provide service and solutions for data and application integration to deliver projects faster at a lower cost. With this high-speed service as strong support, we bring agility to your architecture; enabling companies to connect, mediate and manage services for data delivery in real time.

With our knowledge, we help your data correctly anonymize or pseudonymize with data masking, maintain data quality and foster accountability across teams with data workflows. The concerned in-house data experts help our clients maintain data agility and accelerate time-to-compliance, automate data inventory creation, prepare details about your data subjects that is streaming in from everywhere, legacy systems, shadow IT, CRM systems, device sensors, digital apps, social networks, and much more. We capture and map critical data elements across disparate datasets, and then tracks and traces them with audit trails and data lineage.

Our services cater to the following areas as mentioned below.

Architecting and designing data processing solution

  • Continuous integration/Continuous Delivery.
  • Job compare, audit, testing, debugging, impact analysis and tuning.
  • Metadata bridging for metadata import/export, along with centralized metadata management.
  • Repository manager.
  • ETL and ELT support.
  • Wizards and interactive data viewer
  • Data quality and governance
  • Profiling data and analytics using graphical charts and drill-down data.
  • Automate data quality error resolution and enforce rules.
  • Data cleansing and masking.
  • Data quality portal with monitoring, reporting, and dashboards.
  • Semantic discovery with automatic detection of patterns.
  • Comprehensive survivorship.
  • Data sampling.
  • Enrichment, harmonization, fuzzy matching, and de-duplication.

Connectors

  • AWS, Microsoft Azure, Google Cloud Platform, etc..
  • RDBMS - Oracle, Teradata, Microsoft SQL server and more.
  • SaaS: Marketo, Salesforce, NetSuite and more.
  • Packaged Apps - Microsoft Dynamics, SAP, Sugar CRM etc.
  • Technologies - FTP/SFTP, LDAP, Box, Dropbox, SMTP, etc.
  • Optional 3rd-party address validation services.

Data preparation

  • Import or export and combine data from any databases either in Excel or CSV format.
  • Import or export and combine Parquet, CSV, and AVRO file formats.
  • Export to Tableau, POWER BI, Pentaho.
  • Share data preparations and datasets.
  • Providing support for any data or big data integration flow.
  • Auto-discovery, standardization, auto-profiling, smart suggestions and data visualization.
  • Customization of the semantic type for auto-profiling and standardization.
  • Smart and selective sampling and full-runs.
  • Data tracking and masking with role-based security.
  • Cleansing and enrichment functions.
  • Data Stewardship App for data curation.
  • Define data semantics, data models and data profiling accordingly; define and apply rules.
  • Define and apply rules (survivorship, mass updates).
  • Merge and match data, resolve data errors, and arbitrate on data (classification and certification).
  • Orchestrate and collaborate on activities in campaigns.
  • Define workflows, user roles, and priorities; assign, delegate tasks, tag and comment.
  • Providing embed governance & stewardship in data integration flows, while managing rejects.
  • Embed human certification; MDM processe's error resolution.
  • Take matching decisions that cannot be processed automatically.
  • De-duplicate data at scale with machine learning.
  • Audit and track data error resolution actions. Monitor progress of campaigns. Undo/redo based on business needs.

Advanced data profiling

  • Fraud pattern detection using Benford & Zipf’s Law.
  • Advanced statistics with indicator thresholds.
  • Column set analysis.
  • Advanced matching analysis.
  • Time column correlation analysis.