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Daus Data x OMMA Data

28 of February of 2024

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On the journey towards building data-driven businesses, more and more Big Data processes have been incorporated for analyzing all collected information. Throughout this process, there are numerous barriers to overcome in order to conduct efficient and effective analysis that allows us to obtain valuable insights for decision-making. One of these critical barriers to overcome is Data Quality.

 

 

What is Data Quality?

 

 

Data quality refers to how accurate, consistent, reliable, complete, and relevant the data stored and processed in our data repositories (such as Data Lakes or Data Warehouses) are for the purposes of analysis and decision-making. Data quality plays a crucial role in any Big Data context, as analyses and decisions based on them are heavily influenced by the quality of the underlying data.

Some important aspects of data quality in Big Data include:

 

  • Accuracy: Data must be precise and free from errors.
  • Consistency: Data must be coherent and not contradict each other.
  • Reliability: Data must be reliable and available when needed. This involves maintaining good control over data integrity and ensuring that data is available at all times.
  • Completeness: Data must be complete and not missing crucial values. Missing data can lead to incorrect or biased conclusions.
  • Integrity: Data must maintain their integrity throughout their lifecycle, from acquisition to storage and analysis, which involves protecting them against corruption and unauthorized access.

 

Ensuring data quality in Big Data environments can be challenging due to the volume, velocity, and variety of the data involved. Specific tools and processes are needed to guarantee this quality, such as data cleaning, real-time monitoring, and implementing quality controls throughout the Big Data infrastructure. The OMMA tool can be particularly helpful in this process.

 

 

OMMA

 

 

OMMA Data is a data quality tool that enables organizations to implement quality processes in an agile manner, geared towards non-technical profiles, and with maximum efficiency.

OMMA has the capability to seamlessly integrate into our clients’ existing data processes and can fully incorporate into AWS cloud infrastructure. It leverages AWS’s Big Data services to process information and apply quality rules with great cost and time efficiency, thereby minimizing impact on existing processes and reducing associated costs.

Considering all these factors, at Daus Data, we endorse OMMA for implementing Quality processes for our clients.

 

 

 

Daus Data, AWS Partner of OMMA

 

 

Thanks to the close collaboration between both companies, OMMA has selected Daus as its strategic partner to implement its tool for clients utilizing AWS cloud infrastructure. Daus Data was chosen for its high degree of specialization in Big Data and AI within the AWS platform. This high level of specialization provides confidence to OMMA to collaborate together and continue optimizing the tool, enhancing its high performance on AWS day by day.