The Quick and Easy Guide to Data Preparation

Woman tying her shoes in preparation for a run; illustrates the need for data preparation.

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…

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How to Set Up a Managed Airflow Environment on AWS Alt-Text: “Concept art illustrating Airflow on AWS.

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…

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Quality, Validation, and Observability with Snowflake 

A white snowflake on a blue background, for Snowflake data quality.

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 optimize results from Snowflake, you need to employ a third-party…

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Informatica Data Quality (IDQ): Pros, Cons, and Alternatives

Digital image representing Informatica data quality.

Informatica Data Quality (IDQ): Pros, Cons, and 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…

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The Definitive Guide to the Modern Data Stack

Red cube shapes on a black background representing a modern data stack.

How much value does your organization get from its data? To get the most benefit from your data—and to use data from a variety of sources—you need to implement a modern data stack. With a modern data stack, you’ll be able to gather data from a larger number of sources, provide faster and easier access…

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Why “Data Trustability” is Essential for Building Trust in Smaller and Mid-sized Banks and Financial Services Firms

Seth Rao The recent collapse of lenders 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…

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How to Build a Data Stack That Works for You

Archived boxes representing a modern data stack.

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…

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How to Reduce Data Transfer Costs in AWS

Binary bits and bytes representing 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…

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