“Big Data Analytics Development” for inexpensive and speedy analysis of exponentially growing data


The recent proliferation of smartphones has led to the emergence of massive amounts of data. Moreover, even home appliances such as refrigerators, air conditioners, and vacuum cleaners are connected to the Internet and continue to generate new data. The amount of data held by companies is growing exponentially.

In order to store and process such large and varied data, problems of capacity, cost, and speed have been a constant concern until now. However, with the advent of inexpensive table storage, it is now possible to store information that has not been normalized in its raw form. This makes it possible to provide users with the information they need in a responsive manner.

Effects of Introduction

  • Large volumes of data can be handled at low cost.
  • Normalized data and duplicated data can be stored, and readability is improved.
  • Maximizes system performance when combined with normalized data

Suggested Industries

  • Distribution
  • Information and telecommunications
  • Automotive
  • Advertising
  • Home Appliances
  • Financial Services

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Andaze quickly builds databases with large-scale data storage Azure Table Storage. Please feel free to contact us if your company is troubled with handling big data or has management issues.

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Case Study


Human resource services


Extract necessary information from the huge amount of data sent from IoT terminals


Store raw data from IoT terminals into a large database, Azure Table Storage; aggregate and process human resource data by periodically launching Azure Function to create Json data optimized for display format. The data was then stored in Azure COSMOS DATABASE, which can store flexible data. Necessary information can now be quickly accessed from the inquiry screen.