Snowflake

NOVEMBER 29, 2023

While the former can be solved by tokenization strategies provided by external vendors, the latter mandates the need for patient-level data enrichment to be performed with sufficient guardrails to protect patient privacy, with an emphasis on auditability and lineage tracking.

Metadata 87

Metadata Healthcare Medical Data Storage 87

Data Engineering Podcast

JULY 31, 2022

Summary Data lineage is the roadmap for your data platform, providing visibility into all of the dependencies for any report, machine learning model, or data warehouse table that you are working with. Atlan is the metadata hub for your data ecosystem. Data lineage and metadata systems are a hot topic right now.

IT 100

IT Metadata MongoDB MySQL 100

Snowflake

NOVEMBER 2, 2023

Use cases change, needs change, technology changes – and therefore data infrastructure should be able to scale and evolve with change. We’re committed to giving customers a choice and the ability to adapt while maintaining our core tenets of strong security and governance, excellent performance and simplicity.

Data Lake 94

Data Lake Data Warehouse Cloud Unstructured Data 94

Snowflake

NOVEMBER 11, 2024

Snowflake is committed to doing just that by continually adding features to help our customers simplify how they architect their data infrastructure. At BUILD 2024, we announced several enhancements and innovations designed to help you build and manage your data architecture on your terms. Here’s a closer look.

Data Architecture 77

Data Architecture Architecture Data Lake Kafka 77

Cloudera

JUNE 7, 2022

In the past decade, the amount of structured data created, captured, copied, and consumed globally has grown from less than 1 ZB in 2011 to nearly 14 ZB in 2020. Impressive, but dwarfed by the amount of unstructured data, cloud data, and machine data – another 50 ZB.

IT 112

IT Unstructured Data Data Architecture Government 112

Monte Carlo

MAY 14, 2024

Depending on the quantity of data flowing through an organization’s pipeline — or the format the data typically takes — the right modern table format can help to make workflows more efficient, increase access, extend functionality, and even offer new opportunities to activate your unstructured data.

Data Lake 52

Data Lake Metadata Hadoop Data Governance 52

Cloudera

MARCH 17, 2023

When implementing a data lakehouse, the table format is a critical piece because it acts as an abstraction layer, making it easy to access all the structured, unstructured data in the lakehouse by any engine or tool, concurrently. Some of the popular table formats are Apache Iceberg, Delta Lake, Hudi, and Hive ACID.

Education 64

Education Unstructured Data Data Lake Data Warehouse 64

Monte Carlo

FEBRUARY 21, 2023

In this post, we’ll discuss what, exactly, a data fabric is, how other companies have used it, and how you can build one at your company. Table of Contents What is a data fabric? A data fabric infuses data governance and security across all forms of data, no matter its origin or destination within the organization.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Monte Carlo

FEBRUARY 21, 2023

In this post, we’ll discuss what, exactly, a data fabric is, how other companies have used it, and how you can build one at your company. Table of Contents What is a data fabric? A data fabric infuses data governance and security across all forms of data, no matter its origin or destination within the organization.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Databand.ai

JULY 19, 2023

Data lineage tools are not a new concept. However, their importance has grown significantly in recent years due to the increasing complexity of data architectures and the growing need for data governance and compliance. In this article: Why Are Data Lineage Tools Important?

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

Cloudera

NOVEMBER 17, 2022

We needed a solution to manage our data at scale, to provide greater experiences to our customers. With Cloudera Data Platform, we aim to unlock value faster and offer consistent data security and governance to meet this goal. Aqeel Ahmed Jatoi, Lead – Architecture, Governance and Control, Habib Bank Limited.

Banking 85

Banking Management Data Lake Professional Services 85

Monte Carlo

AUGUST 25, 2023

One advantage of data warehouses is their integrated nature. As fully managed solutions, data warehouses are designed to offer ease of construction and operation. A warehouse can be a one-stop solution, where metadata, storage, and compute components come from the same place and are under the orchestration of a single vendor.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Monte Carlo

APRIL 24, 2023

Traditionally, after being stored in a data lake, raw data was then often moved to various destinations like a data warehouse for further processing, analysis, and consumption. Databricks Data Catalog and AWS Lake Formation are examples in this vein. AWS is one of the most popular data lake vendors.

Data Lake 52

Data Lake Google Cloud Data Warehouse AWS 52

phData: Data Engineering

SEPTEMBER 19, 2023

With the amount of data companies are using growing to unprecedented levels, organizations are grappling with the challenge of efficiently managing and deriving insights from these vast volumes of structured and unstructured data. Want to learn more about data governance?

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

AltexSoft

AUGUST 29, 2023

Instead of relying on traditional hierarchical structures and predefined schemas, as in the case of data warehouses, a data lake utilizes a flat architecture. This structure is made efficient by data engineering practices that include object storage. Watch our video explaining how data engineering works.

Data Lake 52

Data Lake Architecture IT Amazon Web Services 52

Monte Carlo

NOVEMBER 6, 2023

They can range in terms of complexity, ease of use, and feature sets, but all are designed to help illuminate the dark corners of your data repositories, and are a critical component of your data governance practice. Here’s an overview of ten popular data discovery tools (in no particular order) that are available today.

Metadata 40

Metadata Unstructured Data Government Data Governance 40

Cloudera

SEPTEMBER 9, 2022

Imagine quickly answering burning business questions nearly instantly, without waiting for data to be found, shared, and ingested. Imagine independently discovering rich new business insights from both structured and unstructured data working together, without having to beg for data sets to be made available.

Architecture 102

Architecture Metadata Machine Learning Unstructured Data 102

AltexSoft

SEPTEMBER 23, 2021

A data hub serves as a single point of access for all data consumers, whether it be an application, a data scientist, or a business user. So, it also allows for managing data for various tasks, providing centralized governance and data flow control capabilities. Data lake vs data hub.

Architecture 52

Architecture Data Lake Unstructured Data Data Warehouse 52

Data Engineering Podcast

SEPTEMBER 14, 2020

Tree Schema is a data catalog that is making metadata management accessible to everyone. With Tree Schema you can create your data catalog and have it fully populated in under five minutes when using one of the many automated adapters that can connect directly to your data stores.

Process 100

Process Unstructured Data Metadata Data Engineer 100

AltexSoft

FEBRUARY 11, 2023

In the EU, the General Data Protection Regulation (GDPR) sets guidelines for collecting, storing, and processing personal information. This privacy law must be kept in mind when building data architecture. It defines metrics and best practices to ensure data quality as well as data privacy and security.

Data Architect 87

Data Architect Certification Generalist Big Data 87

Towards Data Science

FEBRUARY 9, 2024

Data Store Another significant change from 2021 to 2024 lies in the shift from “Data Warehouse” to “Data Store,” acknowledging the expanding database horizon, including the rise of Data Lakes. Without an orchestration engine, the ability to modularize your data platform and unlock its full potential is limited.

Building 78

Building Transportation Data Lake Metadata 78

AltexSoft

AUGUST 22, 2022

Support for different data types and use cases. A data fabric supports structured, unstructured, and semi-structured data whether it comes in real-time or generated in batches. It is also driven by metadata, which it uses to recognize patterns, map data, and perform continuous analysis. Data and metadata.

Architecture 52

Architecture Metadata Data Lake Machine Learning 52

Monte Carlo

APRIL 1, 2021

As a result, data teams going the the lake or even lakehouse route often struggle to answer critical questions about their data such as: Where does my data live? Data discovery tools and platforms can help. They help data teams answer questions about where to look for data, what data represents, and how it can be used.

Data Lake 52

Data Lake Unstructured Data Data Warehouse Metadata 52

Snowflake

JANUARY 26, 2023

requires multiple categories of data, from time series and transactional data to structured and unstructured data. initiatives, such as improving efficiency and reducing downtime by including broader data sets (both internal and external), offers businesses even greater value and precision in the results.

Data Ingestion 52

Data Ingestion Manufacturing Unstructured Data Architecture 52

AltexSoft

JUNE 26, 2023

From the perspective of data science, all miscellaneous forms of data fall into three large groups: structured, semi-structured, and unstructured. Key differences between structured, semi-structured, and unstructured data. Unstructured data represents up to 80-90 percent of the entire datasphere.

Data Collection 52

Data Collection Machine Learning Unstructured Data Non-relational Database 52

AltexSoft

NOVEMBER 23, 2021

This often results in data inconsistencies and duplications as users demand more data views. Security and governance issues exist as sometimes sensitive data can’t be moved into the cloud or a centralized store, remaining in its native location. Data is commonly delivered in scheduled batches, not on a demand basis.

Process 69

Process Data Lake Metadata Data Warehouse 69

Monte Carlo

JUNE 28, 2022

Traditionally, data lakes held raw data in its native format and were known for their flexibility, speed, and open source ecosystem. By design, data was less structured with limited metadata and no ACID properties. Unity Catalog The Unity Catalog unifies metastores, catalogs, and metadata within Databricks.

Data Lake 52

Data Lake Metadata AWS Data Warehouse 52

AltexSoft

NOVEMBER 10, 2021

In a nutshell, the lakehouse system leverages low-cost storage to keep large volumes of data in its raw formats just like data lakes. At the same time, it brings structure to data and empowers data management features similar to those in data warehouses by implementing the metadata layer on top of the store.

Architecture 52

Architecture Data Lake Data Warehouse Metadata 52

Cloudera

SEPTEMBER 15, 2022

Mark: While most discussions of modern data platforms focus on comparing the key components, it is important to understand how they all fit together. The collection of source data shown on your left is composed of both structured and unstructured data from the organization’s internal and external sources.

Data Lake 82

Data Lake Analytics Application Cloud Storage Architecture 82

Grouparoo

JANUARY 11, 2022

A data warehouse is a unified repository where data from diverse sources undergo aggregation and integration into a usable source of information. To achieve this, a data warehouse will require processes to gather and integrate data, manage data quality, create metadata, and support any regulatory compliance and governance procedures.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Data Engineering Weekly

OCTOBER 23, 2022

I'm one of the early advocates for Data Catalogs and am excited about the possibility of Data Catalogs. The Data Engineering Weekly even published a special Metadata Edition focusing on the historical development of the Data Catalog. Does Data Catalogs live up to the promise?

Data Engineer 52

Data Engineer Data Engineering Engineering Deep Learning 52

Monte Carlo

MAY 31, 2022

Metadata from the data warehouse/lake and from the BI tool of record can then be used to map the dependencies between the tables and dashboards. Spark lineage is the metadata detailing the journey data takes across its lifecycle including source, creator, transformations, and related data sets.

Data Lake 52

Data Lake Building Scala Metadata 52

Monte Carlo

JUNE 14, 2023

Amazon S3 – An object storage service for structured and unstructured data, S3 gives you the compute resources to build a data lake from scratch. Data catalog Some organizations choose to implement data catalog solutions for data governance and compliance use cases.

Data Pipeline 52

Data Pipeline Architecture Data Lake Data Warehouse 52

Knowledge Hut

MAY 9, 2024

Responsibilities Responsibilities of data modelers include validating data models, evaluating existing systems, ensuring data consistency, and optimizing metadata. Skills Required Data modelers must be proficient in SQL, metadata management, data modeling, interpersonal communication, and statistical analysis.

Data Science 52

Data Science Data Architect Data Mining Programming Language 52

AltexSoft

JULY 29, 2022

According to the latest report by Allied Market Research , the Big Data platform will see the biggest rise in adoption in telecommunication, healthcare, and government sectors. Instruments like Apache ZooKeeper and Apache Oozie help better coordinate operations, schedule jobs, and track metadata across a Hadoop cluster.

Hadoop 59

Hadoop Big Data Google Cloud NoSQL 59

AltexSoft

OCTOBER 18, 2022

Medical data labeling. Medical or not, unstructured data — like texts, images, or audio files — require labeling or annotation to train machine learning models. This process involves adding descriptive elements — tags — to pieces of data so that a computer could understand what the image or text is about.

Medical 52

Medical Datasets Machine Learning Hospitality 52

Snowflake

MARCH 30, 2023

Automation , because the same loader patterns are used for both and the same metadata tags are expected from both, meaning the applied date timestamp in the business vault will match up with the raw date timestamp where it came from. Data governance As a data management framework, feature stores must consider data privacy and data governance.

Engineering 84

Engineering Raw Data Data Science Machine Learning 84