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Why Data Quality and Data Governance are Important to Achieve Compliance

Analysts Corner

In this article, we present a brief overview of compliance and regulations, discuss the cost of non-compliance and some related statistics, and the role data quality and data governance play in achieving compliance. The average cost of a data breach among organizations surveyed reached $4.24

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Data Quality Tools: Top 8 for 2023 & Beyond

Astera

What matters is how accurate, complete and reliable that data. Data quality is not just a minor detail; it is the foundation upon which organizations make informed decisions, formulate effective strategies, and gain a competitive edge. to help clean, transform, and integrate your data.

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The Importance of Data Quality in Financial Reporting

Insight Software

Data quality has always been at the heart of financial reporting , but with rampant growth in data volumes, more complex reporting requirements and increasingly diverse data sources, there is a palpable sense that some data, may be eluding everyday data governance and control. Data Quality Audit.

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Interesting statistics around big data, data analysis, and usage

Analysts Corner

Data Analysis (Image created using photo and elements in Canva) Evolution of data and big data Until the advent of computers, limited facts were collected and documented, given the cost and scarcity of resources and effort to capture, store, and maintain them. Food for thought and the way ahead! What do you think?

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How to Build a Data Governance Strategy for Your Organization

Astera

In short, a data governance strategy includes the following: Establishing principles, policies, and procedures for data management. Implementing governance bodies to oversee compliance. Aligning the overarching data strategy. What are data privacy and security protocols? Why is a Data Governance Strategy Needed?

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ETL vs. ELT: A Comprehensive Comparison and Guide to Modern Data Integration Strategies

Analysts Corner

In ELT, raw data is loaded directly into the target system, and the transformation process occurs after the data has been loaded. Advantages of ETL Data Quality: ETL processes typically involve data validation and cleansing, ensuring high data quality and reducing the risk of errors in analysis.

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What is a Data Pipeline?

Insight Software

Data Loading : The transformed data is loaded into the destination system, such as a data warehouse , data lake, or another database, where it can be used for analytics, reporting, or other purposes. By processing data as it arrives, streaming data pipelines support more dynamic and agile decision-making.