DataHub Elevate: efficient data centralisation on BigQuery and Microsoft Azure

problems

The client wants to reduce the challenges it faces when managing plant data: large volume of data, slow access, inconsistency and security gaps.  

YusApi develops a Data Warehouse to transfer data to advanced platforms and offer the customer a centralised solution, improving data analysis and decision making.

Objectives

Develop a complete Data Warehouse to centralise plant data.

Achieve efficient data migration to advanced platforms such as BigQuery and Microsoft Azure.

Facilitate advanced data analytics.

Improve operational efficiency.

  • Develop a complete Data Warehouse to centralise plant data.

  • Achieve efficient data migration to advanced platforms such as BigQuery and Microsoft Azure.

  • Facilitate advanced data analytics.

  • Improve operational efficiency.

Project procedure

1. Planning phase

A Data Warehouse covering all aspects of the plant operation is created and designed.

3. Testing and adjustment phase

In the testing phase, consistency and availability are sought in real time, thus validating the integrity and accessibility of the migrated data.

2. Development phase

To ensure a secure, complete and efficient data transfer, necessary processes are implemented in the data migration.

1. Planning phase

A Data Warehouse covering all aspects of the plant operation is created and designed.

2. Development phase

To ensure a secure, complete and efficient data transfer, necessary processes are implemented in the data migration.

3. Testing and adjustment phase​

In the testing phase, consistency and availability are sought in real time, thus validating the integrity and accessibility of the migrated data.

Results

The client has significantly improved its capabilities in advanced data analysis and provides critical information for strategic decision making.
YusApi positions itself for operational efficiency in the information age.

Business proactivity has increased by

+20%

The speed of data searches has increased by

+70%

Results

The client has significantly improved its capabilities in advanced data analysis and provides critical information for strategic decision making.
YusApi positions itself for operational efficiency in the information age.

Business proactivity has increased by

+20%

The speed of data searches has increased by

+70%

Results

The client has significantly improved its capabilities in advanced data analysis and provides critical information for strategic decision making.
YusApi positions itself for operational efficiency in the information age.

Business proactivity has increased by

+20%

The speed of data searches has increased by

+70%

Sector

  1. Industry.
  2. Automotive.
  3. Energy.
  4. Food and beverage.
  5. Healthcare.
  6. E-commerce.
  7. Aerospace.
  8. Banking.

Technologies used

Microsoft SQL Server

RapidMiner

Python

Microsoft Azure

Google BigQuery

Sector

  1. Industry.
  2. Automotive.
  3. Energy.
  4. Food and beverage.
  5. Healthcare.
  6. E-commerce.
  7. Aerospace.
  8. Banking.

Technologies used​

Microsoft SQL Server

RapidMiner

Python

Microsoft Azure

Google BigQuery

Other use cases

Other use cases

Amazon Seller API Integration in ERP

PLC Code generation automation for Siemens or Schneider

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