Jet Global

JULY 2, 2019

To address the flood of data and the needs of enterprise businesses to store, sort, and analyze that data, a new storage solution has evolved: the data lake. What’s in a Data Lake? Data warehouses do a great job of standardizing data from disparate sources for analysis. Taking a Dip.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

AWS Big Data

DECEMBER 13, 2023

For the past 5 years, BMS has used a custom framework called Enterprise Data Lake Services (EDLS) to create ETL jobs for business users. EDLS job steps and metadata Every EDLS job comprises one or more job steps chained together and run in a predefined order orchestrated by the custom ETL framework.

Metadata 86

Metadata Data Lake Visualization Data Transformation 86

AWS Big Data

AUGUST 16, 2023

Iceberg has become very popular for its support for ACID transactions in data lakes and features like schema and partition evolution, time travel, and rollback. Iceberg captures metadata information on the state of datasets as they evolve and change over time. Choose Create.

Data Lake 77

Data Lake Metadata Snapshot Management 77

AWS Big Data

OCTOBER 4, 2023

Business-driven domains – A DataZone domain represents the distinct boundary of a line of business (LOB) or a business area within an organization that can manage its own data, including its own data assets, its own definition of data or business terminology, and may have its own governing standards.

Metadata 98

Metadata Data Lake Publishing Data Governance 98

AWS Big Data

NOVEMBER 29, 2023

It enables data engineers, data scientists, and analytics engineers to define the business logic with SQL select statements and eliminates the need to write boilerplate data manipulation language (DML) and data definition language (DDL) expressions.

Data Lake 101

Data Lake Management Metrics Data Warehouse 101

AWS Big Data

JANUARY 24, 2023

This solution only replicates metadata in the Data Catalog, not the actual underlying data. To have a redundant data lake using Lake Formation and AWS Glue in an additional Region, we recommend replicating the Amazon S3-based storage using S3 replication , S3 sync, aws-s3-copy-sync-using-batch or S3 Batch replication process.

Data Architecture 65

Data Architecture Metadata Data Lake Snapshot 65

AWS Big Data

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

Data Lake 98

Data Lake Data Warehouse Management Risk 98

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. Second, you must establish a definition of “done.” In DataOps, the definition of done includes more than just some working code. Definition of Done. Monitoring Job Metadata.

Testing 157

Testing Metadata Dashboards Statistics 157

AWS Big Data

DECEMBER 18, 2023

Solution overview One of the common functionalities involved in data pipelines is extracting data from multiple data sources and exporting it to a data lake or synchronizing the data to another database. There are multiple tables related to customers and order data in the RDS database.

Metadata 119

Metadata Visualization Data Lake Data-driven 119

AWS Big Data

APRIL 19, 2023

We split the solution into two primary components: generating Spark job metadata and running the SQL on Amazon EMR. The first component (metadata setup) consumes existing Hive job configurations and generates metadata such as number of parameters, number of actions (steps), and file formats. sql_path SQL file name.

Metadata 78

Metadata Testing Data Lake Consulting 78

Cloudera

MARCH 17, 2023

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. Some of the popular table formats are Apache Iceberg, Delta Lake, Hudi, and Hive ACID.

Unstructured Data 60

Unstructured Data Data Lake Data Warehouse Machine Learning 60

Cloudera

JUNE 7, 2023

By now, almost everyone across the tech landscape has heard of the Zero Trust (ZT) security model, which assumes that every device, application, or user attempting to access a network is not to be trusted (see NIST definitions below). Understanding your data is critical to protecting the data.

Metadata 79

Metadata Data Lake Optimization Modeling 79

AWS Big Data

DECEMBER 21, 2023

To bring their customers the best deals and user experience, smava follows the modern data architecture principles with a data lake as a scalable, durable data store and purpose-built data stores for analytical processing and data consumption.

Data Lake 87

Data Lake Data Warehouse Data-driven B2B 87

Alation

FEBRUARY 13, 2020

These are all good questions and a logical place to start your data cataloging journey. This brief definition makes several points about data catalogs—data management, searching, data inventory, and data evaluation—but all depend on the central capability to provide a collection of metadata.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

AWS Big Data

DECEMBER 5, 2023

A combination of Amazon Redshift Spectrum and COPY commands are used to ingest the survey data stored as CSV files. For the files with unknown structures, AWS Glue crawlers are used to extract metadata and create table definitions in the Data Catalog. Outside of work she enjoys traveling and trying new cuisines.

Measurement 81

Measurement Dashboards Data Warehouse Analytics 81

Alation

APRIL 18, 2023

For any data user in an enterprise today, data profiling is a key tool for resolving data quality issues and building new data solutions. In this blog, we’ll cover the definition of data profiling, top use cases, and share important techniques and best practices for data profiling today.

IT 52

IT Data Quality Metadata Data Governance 52

Cloudera

SEPTEMBER 15, 2022

Mark: The first element in the process is the link between the source data and the entry point into the data platform. At Ramsey International (RI), we refer to that layer in the architecture as the foundation, but others call it a staging area, raw zone, or even a source data lake. What is a data fabric?

Data Lake 79

Data Lake Data Architecture Data-driven Data Warehouse 79

erwin

OCTOBER 31, 2019

What data do we have and where is it? Data is a critical asset used to operate, manage and grow a business. While sometimes at rest in databases, data lakes and data warehouses; a large percentage is federated and integrated across the enterprise, introducing governance, manageability and risk issues that must be managed.

Data Governance 105

Data Governance Metadata Risk Data Lake 105

AWS Big Data

APRIL 25, 2024

In the era of data, organizations are increasingly using data lakes to store and analyze vast amounts of structured and unstructured data. Data lakes provide a centralized repository for data from various sources, enabling organizations to unlock valuable insights and drive data-driven decision-making.

Optimization 65

Optimization Data Lake Cost-Benefit Reporting 65

Timo Elliott

NOVEMBER 30, 2022

Gartner says that data is a liability – after all, it costs you money to collect, and it has risks, the very definition of a liability. To turn it into an asset, you actually have to do something with the data, to change something in the way you do business. And that’s what often goes wrong.

Recreation/Entertainment 98

Recreation/Entertainment Metadata Data Warehouse Cost-Benefit 98

AWS Big Data

FEBRUARY 21, 2023

Any change to the dimension definition results in a lengthy and time-consuming reprocessing of the dimension data, which often results in data redundancy. Another issue is that, when relying merely on dimensional modeling, analysts can’t assure the consistency and accuracy of data sources.

Data Warehouse 64

Data Warehouse Data Lake Cost-Benefit Modeling 64

Octopai

MAY 30, 2019

At the most basic level, data catalogs help you organize your company’s massive datasets. Most enterprises have huge data lakes with millions of touchpoints all living in the dark. They have little in the way of definition or categorization. Folding In Metadata Automation. Scalability.

Metadata 40

Metadata Data Governance Data Lake IoT 40

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. If you want more control over and more value from all your data, join us for a demo of erwin MM.

Data Governance 40

Data Governance Risk Metadata Management 40

AWS Big Data

OCTOBER 2, 2023

JSON data in Amazon Redshift Amazon Redshift enables storage, processing, and analytics on JSON data through the SUPER data type, PartiQL language, materialized views, and data lake queries. This means that when a message is serialized, it includes both the schema definition and the data values.

Cost-Benefit 84

Cost-Benefit Metadata Structured Data Management 84

AWS Big Data

MARCH 3, 2023

Building data lakes from continuously changing transactional data of databases and keeping data lakes up to date is a complex task and can be an operational challenge. You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes.

Data Lake 81

Data Lake Dashboards Metrics Metadata 81

AWS Big Data

JUNE 12, 2023

This job extracts data from the Kafka topics, deserializes it using the schema information from the Data Catalog table, and loads it into Amazon S3. It’s important to note that the schema in the Data Catalog table serves as the source of truth for the AWS Glue streaming job.

Management 77

Management Metadata Testing Internet of Things 77

Domino Data Lab

APRIL 3, 2019

Data governance shows up as the fourth-most-popular kind of solution that enterprise teams were adopting or evaluating during 2019. That’s a lot of priorities – especially when you group together closely related items such as data lineage and metadata management which rank nearby. Definition and Descriptions.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

Alation

JUNE 14, 2021

Indeed, automation is a key element to data catalog features, which enhance data security. Selecting a Data Catalog. To support data security, an effective data catalog should have features, like a business glossary, wiki-like articles, and metadata management. And, finding data is only half the battle.

Data Governance 97

Data Governance Recreation/Entertainment Data Lake Digital Transformation 97

Alation

FEBRUARY 20, 2020

When it was no longer a hard requirement that a physical data model be created upon the ingestion of data, there was a resulting drop in richness of the description and consistency of the data stored in Hadoop. You did not have to understand or prepare the data to get it into Hadoop, so people rarely did.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

Alation

JANUARY 26, 2023

Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? Do they have a system to manage the metadata for given assets? One example is the EU’s General Data Protection Regulation (GDPR).

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

AWS Big Data

AUGUST 28, 2023

Optionally, specify the Amazon S3 storage class for the data in Amazon Security Lake. For more information, refer to Lifecycle management in Security Lake. Review the details and create the data lake. Choose Next. In addition, index templates also contain index-specific settings for a particular index patterns.

Dashboards 52

Dashboards Visualization Metadata Management 52

Ontotext

MARCH 8, 2023

Rich metadata and semantic modeling continue to drive the matching of 50K training materials to specific curricula, leading new, data-driven, audience-based marketing efforts that demonstrate how the recommender service is achieving increased engagement and performance from over 2.3 million users.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

IBM Big Data Hub

OCTOBER 4, 2023

A data lakehouse architecture combines the performance of data warehouses with the flexibility of data lakes, to address the challenges of today’s complex data landscape and scale AI. New insights and relationships are found in this combination. All of this supports the use of AI.

Data Lake 83

Data Lake Metadata Cost-Benefit Data Warehouse 83

Alation

JANUARY 13, 2022

Thoughtworks says data mesh is key to moving beyond a monolithic data lake. Spoiler alert: data fabric and data mesh are independent design concepts that are, in fact, quite complementary. Thoughtworks says data mesh is key to moving beyond a monolithic data lake 2. Gartner on Data Fabric.

Data Lake 59

Data Lake Metadata Data-driven Data Governance 59

Domino Data Lab

AUGUST 8, 2019

Having participated in several Foo Camps—and even co-chaired the Ed Foo series in 2016-17— most definitely, a Foo will turn your head around. I mention this here because there was a lot of overlap between current industry data governance needs and what the scientific community is working toward for scholarly infrastructure.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Cloudera

FEBRUARY 8, 2024

Note that the materialized view definition contains the ‘stored by iceberg’ clause. The snapshotId of the source tables involved in the materialized view are also maintained in the metadata. Let’s create a materialized view that joins the three tables, has filter conditions, and does grouped aggregation.

Snapshot 88

Snapshot Metadata Cost-Benefit Data Warehouse 88