Data Quality and data integrity are both important aspects of data analytics. With the rapid development of data analytics, data can be considered one of the most important assets a business owns. As a result, many organizations collect massive amounts of data for research and marketing purposes. However, the value of this data depends on […]
How Data Integrity Can Maximize Business Value
The last few years have demonstrated how critical it is for businesses to maintain agility and make fast, confident decisions to stay ahead. The resulting economic uncertainty and growth of industry-wide trends, including ESG, cloud migration, and the rise of artificial intelligence and machine learning programs – such as OpenAI’s newly launched GPT-4 model and […]
Database Management Best Practices
Database management best practices promote the efficient use of data throughout the organization. These practices support the collection and storage of quality data, as well as provide easy access to the data by the appropriate people. With today’s data growing in volume and becoming increasingly complex, the intelligent management of data has become a necessity. […]
How to Ensure Data Integrity in Your Organization
We are living in an era of data and analytics. It is the time when organizations are consuming, generating, modifying, and exchanging an insane amount of data. Now, failing to keep track of data that is being consumed, generated, modified, exchanged, or deleted within your organization can have a major impact on your business decisions. […]
What Is Data Integrity?
Data integrity is the totality of a dataset’s validity and consistency over its entire life cycle. In other words, it refers to the correctness and trustworthiness of data. It can be applied to any dataset, from personal information to business records. Data is valid if it contains only correct (accurate) information and can be trusted (reliable). […]
Data Integrity: The Last Mile Problem of Data Observability
Data quality issues have been a long-standing challenge for data-driven organizations. Even with significant investments, the trustworthiness of data in most organizations is questionable at best. Gartner reports that companies lose an average of $14 million per year due to poor data quality. Data observability has been all the rage in data management circles for […]
How to Become a Data Security Analyst
A data security analyst, also known as an information security analyst, is responsible for monitoring and analyzing network activity to identify potential threats or risks. Data security analysts primarily analyze data, conduct research, and use complex analytical tools to address problems related to confidentiality, availability, and integrity of data in an organization. Data security analysts […]
When and Why to Use SQL for Database Analysis
As the world begins to generate more data than ever before, a range of tools has been created that help to deal directly with the rising tide. The market for products and tools that help us deal with data is on a rising trajectory, predicted to reach $103 billion by 2027. One of the leading methods […]
How to Overcome the Plateau of Data Analytics Advancement in Today’s Data Overload
The last few years have seen an astronomical increase in the amount of data being created, stored, and shared. According to the IDC, 64.2 zettabytes of data were created or replicated in 2020 largely due to the dramatic increase in the number of people staying home for work, school, and entertainment. The firm also projects the […]
Data Quality Management 101
Data Quality Management is necessary for dealing with the real challenge of low-quality data. Data Quality Management can stop the waste of time and energy required to deal with inaccurate data by manually reprocessing it. Low-quality data can hide problems in operations and make regulatory compliance a challenge. Good Data Quality Management is essential for […]