Dataversity

APRIL 30, 2021

The goal of digital transformation remains the same as ever – to become more data-driven. We have learned how to gain a competitive advantage by capturing business events in data. Events are data snap-shots of complex activity sourced from the web, customer systems, ERP transactions, social media, […].

Data Pipeline 98

Data Pipeline Data Warehouse Data Governance Data Quality 98

IBM Journey to AI blog

OCTOBER 30, 2023

Thus, DB2 PureScale on AWS equips this insurance company to innovate and make data-driven decisions rapidly, maintaining a competitive edge in a saturated market. The platform provides an intelligent, self-service data ecosystem that enhances data governance, quality and usability.

AWS 95

AWS Data Warehouse AI AI 95

Alation

JULY 30, 2021

A part of that journey often involves moving fragmented on-premises data to a cloud data warehouse. You clearly shouldn’t move everything from your on-premises data warehouses. Otherwise, you can end up with a data swamp. 2: Biz Problem – Making Data Ready for Business Analysis.

Data Warehouse 52

Data Warehouse Data Governance Cloud Data Machine Learning 52

Precisely

JANUARY 25, 2024

There are three potential approaches to mainframe modernization: Data Replication creates a duplicate copy of mainframe data in a cloud data warehouse or data lake, enabling high-performance analytics virtually in real time, without negatively impacting mainframe performance. Best Practice 5.

Data Governance 69

Data Governance Database Cloud Data Data Lakes 69

Pickl AI

NOVEMBER 4, 2024

Key Takeaways Data Engineering is vital for transforming raw data into actionable insights. Key components include data modelling, warehousing, pipelines, and integration. Effective data governance enhances quality and security throughout the data lifecycle. What is Data Engineering?

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Dataconomy

APRIL 6, 2023

This can lead to better data governance practices and, ultimately, more accurate insights. The relationship between data democratization and data governance While data democratization is an important goal, it is also important to ensure that proper data governance practices are in place to ensure that data is managed appropriately.

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Data Governance Data Silos Data Analysis Data Analysis 70

phData

APRIL 29, 2024

Understanding Fivetran Fivetran is a popular Software-as-a-Service platform that enables users to automate the movement of data and ETL processes across diverse sources to a target destination. The phData team achieved a major milestone by successfully setting up a secure end-to-end data pipeline for a substantial healthcare enterprise.

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SQL Data Warehouse Azure Cloud Data 52

Alation

APRIL 19, 2022

In that sense, data modernization is synonymous with cloud migration. Modern data architectures, like cloud data warehouses and cloud data lakes , empower more people to leverage analytics for insights more efficiently. What Is the Role of the Cloud in Data Modernization? Efficient Data Processing.

Data Governance 52

Data Governance Cloud Data Database Data Silos 52

Mlearning.ai

FEBRUARY 16, 2023

The ultimate need for vast storage spaces manifests in data warehouses: specialized systems that aggregate data coming from numerous sources for centralized management and consistency. In this article, you’ll discover what a Snowflake data warehouse is, its pros and cons, and how to employ it efficiently.

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phData

MARCH 11, 2024

For years, marketing teams across industries have turned to implementing traditional Customer Data Platforms (CDPs) as separate systems purpose-built to unlock growth with first-party data. Event Tracking : Capturing behavioral events such as page views, add-to-cart, signup, purchase, subscription, etc.

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Data Warehouse Cloud Data Data Models Data Modeling 52

Alation

APRIL 14, 2022

Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals. This is why, when data moves, it’s imperative for organizations to prioritize data discovery. Data discovery is also critical for data governance , which, when ineffective, can actually hinder organizational growth.

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Data Governance ML ML Cloud Data 59

Pickl AI

AUGUST 11, 2024

These tables are called “factless fact tables” or “junction tables” They are used for modelling many-to-many relationships or for capturing timestamps of events. Ensuring Data Consistency Maintaining data consistency across multiple fact tables can be challenging, especially when dealing with conformed dimensions.

Data Quality 52

Data Quality Data Warehouse Data Governance Analytics 52

Alation

AUGUST 26, 2021

It asks much larger questions, which flesh out an organization’s relationship with data: Why do we have data? Why keep data at all? Answering these questions can improve operational efficiencies and inform a number of data intelligence use cases, which include data governance, self-service analytics, and more.

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Precisely

MAY 13, 2024

Wide support for enterprise-grade sources and targets Large organizations with complex IT landscapes must have the capability to easily connect to a wide variety of data sources. Whether it’s a cloud data warehouse or a mainframe, look for vendors who have a wide range of capabilities that can adapt to your changing needs.

Data Governance 52

Data Governance Data Pipeline Cloud Data Data Quality 52

Alation

FEBRUARY 13, 2020

This was an eventful year in the world of data and analytics. billion merger of Cloudera and Hortonworks, the widely scrutinized GDPR (General Data Protection Regulation), or the Cambridge Analytica scandal that rocked Facebook. Amid the headline grabbing news, 2018 will also be remembered as the year of the data catalog.

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Data Governance Machine Learning Machine Learning Analytics 52

Alation

MARCH 1, 2022

Lineage helps them identify the source of bad data to fix the problem fast. Manual lineage will give ARC a fuller picture of how data was created between AWS S3 data lake, Snowflake cloud data warehouse and Tableau (and how it can be fixed). Time is money,” said Leonard Kwok, Senior Data Analyst, ARC.

Data Warehouse 52

Data Warehouse Data Lakes Cloud Data Database 52

Pickl AI

JULY 30, 2024

Flow-Based Programming : NiFi employs a flow-based programming model, allowing users to create complex data flows using simple drag-and-drop operations. This visual representation simplifies the design and management of data pipelines. Guaranteed Delivery : NiFi ensures that data delivered reliably, even in the event of failures.

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phData

JANUARY 24, 2024

Fivetran includes features like data movement, transformations, robust security, and compatibility with third-party tools like DBT, Airflow, Atlan, and more. Its seamless integration with popular cloud data warehouses like Snowflake can provide the scalability needed as your business grows.

Data Warehouse 52

Data Warehouse Data Pipeline Data Governance Cloud Data 52

Alation

FEBRUARY 13, 2020

Overcoming the challenges of data catalog adoption takes more than patience and persistence. You’ll need a plan that recognizes adoption as a process that unfolds over time—not an event that happens at a point in time. People – Which data stakeholders will you bring on board at what times? How will data curation be funded?

Data Governance 52

Data Governance Data Analysis Data Analysis Data Preparation 52

Pickl AI

MAY 11, 2023

Data Warehousing To store a large volume of data, every company needs to switch to Data Warehouse. It can be cloud-based or deploy a physical infrastructure catering to data warehousing. The latter is, however, costly, but cloud-based data storage is cheaper, more effective and more efficient.

Data Warehouse 52

Data Warehouse Data Governance Big Data Big Data 52

Pickl AI

AUGUST 9, 2024

Data Warehousing Solutions Tools like Amazon Redshift, Google BigQuery, and Snowflake enable organisations to store and analyse large volumes of data efficiently. Students should learn about the architecture of data warehouses and how they differ from traditional databases.

Big Data 52

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ODSC - Open Data Science

JANUARY 18, 2024

They’ll also work with software engineers to ensure that the data infrastructure is scalable and reliable. These professionals will work with their colleagues to ensure that data is accessible, with proper access. You can also get data science training on-demand wherever you are with our Ai+ Training platform.

Data Engineering 52

Data Engineering Data Engineering Data Engineer Data Engineering 52

phData

MAY 13, 2024

Difficulty in moving non-SAP data into SAP for analytics which encourages data silos and shadow IT practices as business users search for ways to extract the data (which has data governance implications).

Database 52

Database Analytics Analytics Machine Learning 52

DagsHub

AUGUST 23, 2024

We already know that a data quality framework is basically a set of processes for validating, cleaning, transforming, and monitoring data. Data Governance Data governance is the foundation of any data quality framework. It primarily caters to large organizations with complex data environments.

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Data Quality Data Governance Machine Learning Machine Learning 52

phData

FEBRUARY 27, 2024

The Snowflake Data Cloud is a cloud-based data warehouse that is becoming increasingly popular among businesses of all sizes. Establish data governance guidelines. Define clear data governance guidelines to ensure data consistency, integrity, and security across multiple accounts.

Database 52

Database Data Governance Data Silos Data Warehouse 52

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. But what does this mean from a practitioner perspective? Happy to chat.

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phData

JANUARY 15, 2024

It accurately recognizes diverse data types and supports various table structures, excluding certain data types like GEOGRAPHY and BINARY. The process computes costs based on data volume. It enhances data governance by introducing a tagging mechanism.

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Data Governance Database Data Warehouse Cloud Computing 52

phData

OCTOBER 25, 2024

Data Quality Monitoring implements quality checks in operational data processes to ensure that the data meets pre-defined standards and business rules. This results in poor credibility and data consistency after some time, leading businesses to mistrust the data pipelines and processes. Contact phData Today!

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Data Quality Data Pipeline Data Governance Database 52

Flipboard

MARCH 21, 2025

Traditionally, answering this question would involve multiple data exports, complex extract, transform, and load (ETL) processes, and careful data synchronization across systems. The existing Data Catalog becomes the Default catalog (identified by the AWS account number) and is readily available in SageMaker Lakehouse.

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SQL Data Analyst Data Warehouse AWS 141

The MLOps Blog

MARCH 15, 2023

Data governance: Ensure that the data used to train and test the model, as well as any new data used for prediction, is properly governed. 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.

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Alation

FEBRUARY 13, 2020

And celebrating the ability for Machine Learning Data Catalogs to support data culture in every enterprise. Join us at one of our upcoming events and share your story of human-machine collaboration to create data culture. Follow us at #MLDC as we tour the world. – John F.

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Machine Learning Machine Learning Big Data Big Data 52

Data Science Blog

MARCH 30, 2023

Der andere Teil des Process Minings ist jedoch noch viel wesentlicher, denn es handelt sich dabei um das Fundament der Analyse: Die Datenmodellierung des Event Logs. Jedes Process Mining Tool benötigt pro Use Case mindestens ein Event Log. Idealerweise werden nur fertige Event-Logs bzw. Celonis Process Mining) übertragen.

Data Warehouse 147

Data Warehouse Business Intelligence Business Intelligence Power BI 147

Data Science Blog

SEPTEMBER 3, 2024

Dabei darf gerne in Erinnerung gerufen werden, dass Process Mining im Kern eine Graphenanalyse ist, die ein Event Log in Graphen umwandelt, Aktivitäten (Events) stellen dabei die Knoten und die Prozesszeiten die Kanten dar, zumindest ist das grundsätzlich so. Es handelt sich dabei also um eine Analysemethodik und nicht um ein Tool.

Data Science 130

Data Science Power BI Azure Data Warehouse 130

phData

SEPTEMBER 27, 2024

Methods that allow our customer data models to be as dynamic and flexible as the customers they represent. In this guide, we will explore concepts like transitional modeling for customer profiles, the power of event logs for customer behavior, persistent staging for raw customer data, real-time customer data capture, and much more.

Data Models 52

Data Models Data Modeling Apache Kafka Data Lakes 52

Alation

APRIL 14, 2023

Practitioners and hands-on data users were thrilled to be there, and many connected as they shared their progress on their own data stack journeys. People were familiar with the value of a data catalog (and the growing need for data governance ), though many admitted to being somewhat behind on their journeys.

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