Cloudera

MARCH 17, 2023

The one key component that is missing is a common, shared table format, that can be used by all analytic services accessing the lakehouse data. The table format provides the necessary structure for the unstructured data that is missing in a data lake, using a schema or metadata definition, to bring it closer to a data warehouse.

Education 60

Education Unstructured Data Data Lake Data Warehouse 60

Towards Data Science

APRIL 6, 2023

Data types : Anomaly detection looks different depending on if the data is structured, semi-structured, or unstructured, so it’s important to know what you’re working with. When it comes to detecting anomalies in unstructured data (e.g.,

Unstructured Data 81

Unstructured Data Metadata Data Coding 81

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 106

IT Unstructured Data Data Architecture Government 106

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? As your team builds your data fabric, make sure you have a designated way to collect the various metadata associated with your data inputs.

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? As your team builds your data fabric, make sure you have a designated way to collect the various metadata associated with your data inputs.

Data Architecture 52

Data Architecture Architecture Metadata Unstructured Data 52

Knowledge Hut

DECEMBER 21, 2023

In the present-day world, almost all industries are generating humongous amounts of data, which are highly crucial for the future decisions that an organization has to make. This massive amount of data is referred to as “big data,” which comprises large amounts of data, including structured and unstructured data that has to be processed.

Hadoop 52

Hadoop Big Data NoSQL Unstructured Data 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

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? Check out our Data Governance on Snowflake blog!

Data Lake 52

Data Lake Process Metadata Data Warehouse 52

Databand.ai

JULY 19, 2023

This feature is critical in today’s data-driven business environment, where data may originate from a variety of sources and undergo numerous transformations before reaching its final destination. Metadata Management Metadata, or ‘data about data’, is a crucial component of data management.

Pipeline-centric 52

Pipeline-centric Data Governance Metadata Government 52

AltexSoft

FEBRUARY 11, 2023

What’s more, investing in data products, as well as in AI and machine learning was clearly indicated as a priority. This suggests that today, there are many companies that face the need to make their data easily accessible, cleaned up, and regularly updated.

Data Architect 87

Data Architect Certification Generalist Big Data 87

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 Engineering 100

Snowflake

APRIL 5, 2023

With Snowflake’s support for multiple data models such as dimensional data modeling and Data Vault, as well as support for a variety of data types including semi-structured and unstructured data, organizations can accommodate a variety of sources to support their different business use cases.

Data Warehouse 52

Data Warehouse Healthcare Unstructured Data Metadata 52

Cloudera

JUNE 25, 2021

Using easy-to-define policies, Replication Manager solves one of the biggest barriers for the customers in their cloud adoption journey by allowing them to move both tables/structured data and files/unstructured data to the CDP cloud of their choice easily. Specification of access conditions for specific users and groups.

Cloud 68

Cloud Data Lake Cloud Storage Metadata 68

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

Snowflake

JANUARY 26, 2023

Accessing data from the manufacturing shop floor is one of the key topics of interest with the majority of cloud platform vendors due to the pace of Industry 4.0 requires multiple categories of data, from time series and transactional data to structured and unstructured data. Industry 4.0, By leveraging I4.0

Data Ingestion 52

Data Ingestion Manufacturing Unstructured Data Architecture 52

Cloudera

SEPTEMBER 17, 2020

By enabling their event analysts to monitor and analyze events in real time, as well as directly in their data visualization tool, and also rate and give feedback to the system interactively, they increased their data to insight productivity by a factor of 10. . Our solution: Cloudera Data Visualization.

Unstructured Data 80

Unstructured Data Pharmaceutical Data Warehouse MySQL 80

Grouparoo

JANUARY 11, 2022

When it comes to storing large volumes of data, a simple database will be impractical due to the processing and throughput inefficiencies that emerge when managing and accessing big data. This article looks at the options available for storing and processing big data, which is too large for conventional databases to handle.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Raw Data 52

Silectis

JANUARY 3, 2021

BI (Business Intelligence) Strategies and systems used by enterprises to conduct data analysis and make pertinent business decisions. Big Data Large volumes of structured or unstructured data. Data Catalog An organized inventory of data assets relying on metadata to help with data management.

Data Engineering 40

Data Engineering Data Engineer Engineering Hadoop 40

Knowledge Hut

NOVEMBER 28, 2023

Hence, learning and developing the required data engineer skills set will ensure a better future and can even land you better salaries in good companies anywhere in the world. After all, data engineer skills are required to collect data, transform it appropriately, and make it accessible to data scientists.

Data Engineering 52

Data Engineering Data Engineer Engineering Generalist 52

Cloudera

SEPTEMBER 1, 2020

DDE also makes it much easier for application developers or data workers to self-service and get started with building insight applications or exploration services based on text or other unstructured data (i.e. data best served through Apache Solr). Coordinates distribution of data and metadata, also known as shards.

Cloud Storage 66

Cloud Storage Unstructured Data AWS Analytics Application 66

Knowledge Hut

SEPTEMBER 29, 2023

The Azure Data Engineer Certification test evaluates one's capacity for organizing and putting into practice data processing, security, and storage, as well as their capacity for keeping track of and maximizing data processing and storage. They control and safeguard the flow of organized and unstructured data from many sources.

Certification 52

Certification Data Engineering Data Engineer Engineering 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 78

Data Lake Analytics Application Cloud Storage Architecture 78

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

Knowledge Hut

JULY 26, 2023

It is made up of tables that carry data in rows and columns. Data Access Layer: The data access layer function is to create a connection between the application and the database. They hold data in the form of objects that can contain both data and behaviour. Database Software- Document Store (e.g.-MongoDB):

Database 52

Database NoSQL Telecommunication MongoDB 52

Ascend.io

AUGUST 31, 2023

For example, unlike traditional platforms with set schemas, data lakes adapt to frequently changing data structures at points where the data is loaded , accessed, and used. As a result, transformation processing inside data warehouses is becoming more accessible, and maintaining a separate data lake is no longer needed.

Data Lake 52

Data Lake ETL Tools Data Warehouse Data Pipeline 52

Cloudera

AUGUST 30, 2018

Consider the following practices that, until recently, were relegated to the R&D department: Data-driven decision making – the collection and analysis of data to guide decisions that improve success.

Unstructured Data 40

Unstructured Data Machine Learning Data Warehouse BI 40

ProjectPro

OCTOBER 15, 2014

Does not have a dedicated metadata database. Get FREE Access to Data Analytics Example Codes for Data Cleaning, Data Munging, and Data Visualization Hadoop technology is the buzz word these days but most of the IT professionals still are not aware of the key components that comprise the Hadoop Ecosystem.

Hadoop 52

Hadoop Unstructured Data Java SQL 52

Snowflake

NOVEMBER 29, 2023

In medicine, lower sequencing costs and improved clinical access to NGS technology has been shown to increase diagnostic yield for a range of diseases, from relatively well-understood Mendelian disorders, including muscular dystrophy and epilepsy , to rare diseases such as Alagille syndrome.

Metadata 84

Metadata Healthcare Medical Data Storage 84

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

Snowflake

NOVEMBER 2, 2023

To give customers flexibility for how they fit Snowflake into their architecture, Iceberg Tables can be configured to use either Snowflake or an external service like AWS Glue as the tables’s catalog to track metadata, with an easy one-line SQL command to convert to Snowflake in a metadata-only operation.

Data Lake 92

Data Lake Data Warehouse Cloud Unstructured Data 92

ProjectPro

FEBRUARY 8, 2023

When Glue receives a trigger, it collects the data, transforms it using code that Glue generates automatically, and then loads it into Amazon S3 or Amazon Redshift. Then, Glue writes the job's metadata into the embedded AWS Glue Data Catalog. being data exactly matches the classifier, and 0.0 Why Use AWS Glue?

AWS 98

AWS Scala Metadata Data Lake 98

Data Engineering Podcast

NOVEMBER 27, 2022

Summary The data ecosystem has been growing rapidly, with new communities joining and bringing their preferred programming languages to the mix. This has led to inefficiencies in how data is stored, accessed, and shared across process and system boundaries. Atlan is the metadata hub for your data ecosystem.

Data Process 100

Data Process Process Metadata Business Intelligence 100

Monte Carlo

JANUARY 23, 2024

Gen AI can whip up serviceable code in moments — making it much faster to build and test data pipelines. Today’s LLMs can already process enormous amounts of unstructured data, automating much of the monotonous work of data science. But what does that mean for the roles of data engineers and data scientists going forward?

Pipeline-centric 52

Pipeline-centric Database-centric Metadata Unstructured Data 52

Snowflake

JANUARY 22, 2024

As part of that transition, Fidelity has consolidated its analytics data into its Enterprise Analytics Platform, which is engineered using the Snowflake Data Cloud, making it easier for teams and departments across the company to access the data they need. Historically, the platform was housed in physical servers.

Engineering 64

Engineering Data Lake Unstructured Data Metadata 64

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. This metadata is then utilized to manage, monitor, and foster the growth of the platform.

Building 81

Building Transportation Data Lake Metadata 81

Monte Carlo

NOVEMBER 6, 2023

With features like automated data classification, data quality checks , and data lineage , Collibra helps provide both accessibility and an extra level of reliability for your data. It offers a 360-degree view of your data, including data lineage, relationships, and rich metadata.

Metadata 40

Metadata Unstructured Data Government Data Governance 40