Dataconomy

DECEMBER 17, 2024

This blog post explores effective strategies for gathering requirements in your data project. Whether you are a data analyst , project manager, or data engineer, these approaches will help you clarify needs, engage stakeholders, and ensure requirements gathering techniques to create a roadmap for success.

Data Quality 91

Data Quality Power BI Data Engineering Data Engineer 91

Pickl AI

OCTOBER 19, 2023

Data quality plays a significant role in helping organizations strategize their policies that can keep them ahead of the crowd. Hence, companies need to adopt the right strategies that can help them filter the relevant data from the unwanted ones and get accurate and precise output.

Data Quality 52

Data Quality Data Governance Data Warehouse Machine Learning 52

Data Science Dojo

SEPTEMBER 6, 2023

M aintaining the security and governance of data within a data warehouse is of utmost importance. Data ownership extends beyond mere possession—it involves accountability for data quality, accuracy, and appropriate use. This includes defining data formats, naming conventions, and validation rules.

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Data Warehouse Data Governance Data Quality ETL 195

Dataversity

AUGUST 30, 2021

DataOps, which focuses on automated tools throughout the ETL development cycle, responds to a huge challenge for data integration and ETL projects in general. ETL projects are increasingly based on agile processes and automated testing. extract, transform, load) projects are often devoid of automated testing.

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DataOps ETL Data Pipeline Data Warehouse 52

Pickl AI

JUNE 7, 2024

Summary: Choosing the right ETL tool is crucial for seamless data integration. Top contenders like Apache Airflow and AWS Glue offer unique features, empowering businesses with efficient workflows, high data quality, and informed decision-making capabilities. Also Read: Top 10 Data Science tools for 2024.

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ETL Data Quality Data Pipeline Data Warehouse 40

Dataversity

APRIL 24, 2025

Business insights are only as good as the accuracy of the data on which they are built. According to Gartner, data quality is important to organizations in part because poor data quality costs organizations at least $12.9 million a year on average.

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Data Quality Data Pipeline ETL Database 52

AWS Machine Learning Blog

OCTOBER 9, 2024

The service, which was launched in March 2021, predates several popular AWS offerings that have anomaly detection, such as Amazon OpenSearch , Amazon CloudWatch , AWS Glue Data Quality , Amazon Redshift ML , and Amazon QuickSight. You can review the recommendations and augment rules from over 25 included data quality rules.

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AWS ML ML Data Quality 99

Data Science Dojo

MARCH 1, 2024

Read this blog on LlamaIndex to learn more in detail Features of LlamaIndex: LlamaIndex is an innovative tool designed to enhance the utilization of large language models (LLMs) by seamlessly connecting your data with the powerful computational capabilities of these models.

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ETL Artificial Intelligence Artificial Intelligence Data Quality 307

Pickl AI

AUGUST 31, 2023

However, analysis of data may involve partiality or incorrect insights in case the data quality is not adequate. Accordingly, the need for Data Profiling in ETL becomes important for ensuring higher data quality as per business requirements. What is Data Profiling in ETL?

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Data Profiling ETL Data Quality Data Wrangling 52

IBM Journey to AI blog

OCTOBER 22, 2024

The ability to effectively deploy AI into production rests upon the strength of an organization’s data strategy because AI is only as strong as the data that underpins it. This strategy helps organizations optimize data usage, expand into new markets, and increase revenue.

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Data Silos Data Pipeline DataOps Business Intelligence 102

AWS Machine Learning Blog

FEBRUARY 18, 2025

To handle the log data efficiently, raw logs were centralized into an Amazon Simple Storage Service (Amazon S3) bucket. An Amazon EventBridge schedule checked this bucket hourly for new files and triggered log transformation extract, transform, and load (ETL) pipelines built using AWS Glue and Apache Spark.

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AWS Database ETL AI 78

Data Science Blog

JUNE 27, 2023

The batch views within the Lambda architecture allow for the application of more complex or resource-intensive rules, resulting in superior data quality and reduced bias over time. On the other hand, the real-time views provide immediate access to the most current data. The post Big Data – Lambda or Kappa Architecture?

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Big Data Big Data Apache Kafka Database 130

Dataversity

SEPTEMBER 21, 2021

In my first business intelligence endeavors, there were data normalization issues; in my Data Governance period, Data Quality and proactive Metadata Management were the critical points. The post The Declarative Approach in a Data Playground appeared first on DATAVERSITY. It is something so simple and so powerful.

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Data Governance Business Intelligence Business Intelligence Data Quality 98

Pickl AI

DECEMBER 25, 2024

Introduction In today’s data-driven world, organisations strive to leverage their data for informed decision-making and strategic planning. However, many face significant barriers in the form of data silos. Key Takeaways Data silos limit access to critical information across departments.

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Data Silos Database Data Quality ETL 52

IBM Journey to AI blog

MAY 9, 2024

At the same time, implementing a data governance framework poses some challenges, such as data quality issues, data silos security and privacy concerns. Data quality issues Positive business decisions and outcomes rely on trustworthy, high-quality data. ” Michael L.,

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Data Governance Data Silos Data Quality Predictive Analytics 85

AWS Machine Learning Blog

FEBRUARY 21, 2025

Previously, he was a Data & Machine Learning Engineer at AWS, where he worked closely with customers to develop enterprise-scale data infrastructure, including data lakes, analytics dashboards, and ETL pipelines. He specializes in designing, building, and optimizing large-scale data solutions.

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AWS Natural Language Processing Machine Learning Machine Learning 130

IBM Journey to AI blog

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

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AWS Database ETL AI 93

Pickl AI

JUNE 28, 2023

But, this data is often stored in disparate systems and formats. Here comes the role of Data Mining. Read this blog to know more about Data Integration in Data Mining, The process encompasses various techniques that help filter useful data from the resource. Thereby, improving data quality and consistency.

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Data Mining Data Mining Data Mining ETL 52

Dataversity

NOVEMBER 15, 2023

Those who want to design universal data pipelines and ETL testing tools face a tough challenge because of the vastness and variety of technologies: Each data pipeline platform embodies a unique philosophy, architectural design, and set of operations.

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Data Pipeline ETL Data Governance Data Quality 59

IBM Journey to AI blog

APRIL 20, 2023

Data engineers can scan data connections into IBM Cloud Pak for Data to automatically retrieve a complete technical lineage and a summarized view including information on data quality and business metadata for additional context.

Database 86

Database Data Engineering Data Engineering Data Engineer 86

AWS Machine Learning Blog

JANUARY 17, 2024

To obtain such insights, the incoming raw data goes through an extract, transform, and load (ETL) process to identify activities or engagements from the continuous stream of device location pings. As part of the initial ETL, this raw data can be loaded onto tables using AWS Glue.

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Clustering AWS ML ML 137

Pickl AI

JUNE 11, 2024

But raw data alone isn’t enough to gain valuable insights. This is where data warehouses come in – powerful tools designed to transform raw data into actionable intelligence. This blog delves into the world of data warehouses, exploring their functionality, key features, and the latest innovations.

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Data Warehouse ETL Data Mining Data Mining 52

phData

JUNE 23, 2023

With its built-in data lineage capabilities, Snowflake allows organizations to directly capture, visualize, and analyze data lineage within its cloud-native environment. Data Integrity and Trust – Data lineage helps identify potential data quality issues, troubleshoot data discrepancies, and ensure data integrity.

Data Quality 52

Data Quality Data Governance ETL Database 52

Pickl AI

MARCH 19, 2025

Data engineering is all about collecting, organising, and moving data so businesses can make better decisions. Handling massive amounts of data would be a nightmare without the right tools. In this blog, well explore the best data engineering tools that make data work easier, faster, and more reliable.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

phData

OCTOBER 17, 2023

In our previous blog , we discussed how Fivetran and dbt scale for any data volume and workload, both small and large. Now, you might be wondering what these tools can do for your data team and the efficiency of your organization as a whole. Can these tools help reduce the time our data engineers spend fixing things?

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ETL Data Pipeline Data Engineering Data Engineer 52

Precisely

MARCH 12, 2024

That’s where data enrichment comes into the picture. In this blog post, we’ll explain what data enrichment is, why you need it, how it works, and how B2B companies can use enriched data to drive results. What is data enrichment? Better data quality. Customer data quality decays quickly.

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Data Quality ETL Analytics Analytics 52

Pickl AI

JULY 8, 2024

Summary: This blog explains how to build efficient data pipelines, detailing each step from data collection to final delivery. Introduction Data pipelines play a pivotal role in modern data architecture by seamlessly transporting and transforming raw data into valuable insights.

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Data Pipeline Data Quality Database Apache Kafka 52

AWS Machine Learning Blog

SEPTEMBER 18, 2024

Hosted on Amazon ECS with tasks run on Fargate, this platform streamlines the end-to-end ML workflow, from data ingestion to model deployment. This blog post delves into the details of this MLOps platform, exploring how the integration of these tools facilitates a more efficient and scalable approach to managing ML projects.

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IBM Journey to AI blog

JULY 3, 2024

To power AI and analytics workloads across your transactional and purpose-built databases, you must ensure they can seamlessly integrate with an open data lakehouse architecture without duplication or additional extract, transform, load (ETL) processes. Effective data quality management is crucial to mitigating these risks.

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AI AI Data Quality Database 45

Pickl AI

JULY 25, 2024

Summary: Data ingestion is the process of collecting, importing, and processing data from diverse sources into a centralised system for analysis. This crucial step enhances data quality, enables real-time insights, and supports informed decision-making. It supports both batch and real-time processing.

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Apache Kafka Data Lakes Data Warehouse Data Quality 52

The MLOps Blog

MARCH 15, 2023

This is a blog post from AWS to optimize cloud services costs. For small-scale/low-value deployments, there might not be many items to focus on, but as the scale and reach of deployment go up, data governance becomes crucial. This includes data quality, privacy, and compliance.

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AWS Machine Learning Blog

NOVEMBER 29, 2023

For instance, a notebook that monitors for model data drift should have a pre-step that allows extract, transform, and load (ETL) and processing of new data and a post-step of model refresh and training in case a significant drift is noticed. Run the notebooks The sample code for this solution is available on GitHub.

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ML ML Data Scientist Python 121

Pickl AI

AUGUST 9, 2024

Summary: This blog delves into hierarchies in dimensional modelling, highlighting their significance in data organisation and analysis. Real-world examples illustrate their application, while tools and technologies facilitate effective hierarchical data management in various industries.

Data Warehouse 52

Data Warehouse Data Quality ETL Business Intelligence 52

Pickl AI

JULY 25, 2023

Data engineers are essential professionals responsible for designing, constructing, and maintaining an organization’s data infrastructure. They create data pipelines, ETL processes, and databases to facilitate smooth data flow and storage. Data Warehousing: Amazon Redshift, Google BigQuery, etc.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

Pickl AI

AUGUST 11, 2024

Summary: This blog discusses best practices for designing effective fact tables in dimensional models. Additionally, it addresses common challenges and offers practical solutions to ensure that fact tables are structured for optimal data quality and analytical performance.

Data Quality 52

Data Quality Data Warehouse Data Governance Analytics 52

Pickl AI

MARCH 3, 2025

Business Intelligence Analysts are the skilled artisans who transform this raw data into valuable insights, empowering organizations to make strategic decisions and stay ahead of the curve. Key Takeaways BI Analysts convert data into actionable insights for strategic business decisions. Identifying and resolving data quality issues.

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Business Intelligence Business Intelligence Data Analyst Data Visualization 52

The MLOps Blog

MARCH 15, 2023

Scalability : A data pipeline is designed to handle large volumes of data, making it possible to process and analyze data in real-time, even as the data grows. Data quality : A data pipeline can help improve the quality of data by automating the process of cleaning and transforming the data.

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