Posts by Seth Rao
What is Data Preparation? A 6-Step Guide to Clean, Transform, and Optimize Data for Analysis
Do you know why data preparation is important to your organization? Poor-quality or “dirty” data can result in unreliable analysis and ill-informed decision-making. This problem worsens when data flows into your system from multiple, unstandardized sources. The only way to ensure accurate data analysis is to prepare all ingested data to meet specified data quality…
Read More10 Essential Steps to Set Up AWS Managed Airflow for Optimized Workflow Management
Harnessing the power of cloud-based workflow management has become indispensable in modern IT environments. Amazon Web Services (AWS) offers Amazon Managed Workflows for Apache Airflow (MWAA), a crucial tool that simplifies complex computational workflows and enables Managed Airflow on AWS. In 2022, AWS’s revenue surpassed $80 billion, indicating its prominent role in the growing cloud…
Read MoreImprove Snowflake Data Quality With Robust Validation, Observability, and Ingestion
How Can You Improve Snowflake Data Quality With Advanced Solutions? Do you know how to get optimal use from Snowflake? Snowflake is a data ingestion and warehousing solution used by more than 7,000 companies worldwide. It makes it easy to ingest, retrieve, and analyze data from multiple sources, but it doesn’t guarantee data quality. To…
Read MoreInformatica Data Quality: What It Does, Key Uses, Competitors, and Top Alternatives
Many enterprises worldwide rely on IDQ to monitor and manage the quality of data they use for day-to-day operations. IDQ – one of the oldest data quality management solutions available today – provides a platform for data analysis and data quality validation by writing rules. Although IDQ is a popular and trusted data quality tool,…
Read MoreUnderstanding the Modern Data Stack: Key Components & Benefits
How much value does your organization get from its data? To maximize its potential, you need a modern data stack—a cloud-based collection of tools that enables seamless data integration, storage, and analysis. A modern data stack allows businesses to gather data from multiple sources and process it with greater speed and flexibility compared to traditional…
Read MoreWhy Data Trustability in Banking is Essential for Mid-Sized Banks and Financial Services Firms
Introduction: The Trust Crisis Facing Mid-Sized Banks In the US has tested Americans’ faith in regional and community banks that supply credit to a significant portion of the country’s entrepreneurs and businesses. Deposits have flooded into megabanks, leading to a significant decline in smaller banks’ deposits, which could have long-lasting repercussions for the communities served…
Read MoreHow to Build a Data Stack That Ensures Data Quality
How does your organization manage the volumes of data ingested each day? The most effective way to ingest and manage large amounts of data is with a modern data stack. To build a data stack that meets your business needs, follow the five essential steps to ensuring the highest quality, most useable data possible outlined…
Read MoreHow to Reduce Data Transfer Costs in AWS?
One out of three organizations today use Amazon Web services (AWS) to store and manage their online data and applications. Unfortunately, Amazon charges hefty fees to transfer between locations, whether that’s to your on-premises network or to users on the public Internet. Learning how to reduce AWS data transfer costs is essential in minimizing expenses…
Read MoreData Mesh vs Data Lake: Understanding Key Architecture Differences, Benefits, and Trustability
Data Lake relies on a centralized data repository, while Data Mesh decentralizes data storage and management. It’s a war between different philosophies of data architecture, but your organization will eventually have to choose sides. So which is better for your business? Which is better for quick decisions and which is better for more reliable and…
Read More10 Leading Data Observability Tools Trusted by Top Tech Companies in 2025
In today’s data-driven world, ensuring the health and reliability of data systems is paramount for any organization. Data observability tools play a crucial role in achieving this by providing comprehensive monitoring and analysis of data flows and system performance. These tools help identify and resolve data issues in real-time, ensuring that your data is accurate,…
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