erwin

SEPTEMBER 17, 2020

According to erwin’s “2020 State of Data Governance and Automation” report , close to 70 percent of data professional respondents say they spend an average of 10 or more hours per week on data-related activities, and most of that time is spent searching for and preparing data.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 110

Metadata Data Lake Visualization Data Transformation 110

AWS Big Data

OCTOBER 11, 2023

Traditionally, such a legacy call center analytics platform would be built on a relational database that stores data from streaming sources. Data transformations through stored procedures and use of materialized views to curate datasets and generate insights is a known pattern with relational databases.

Management 130

Management Metadata Analytics Dashboards 130

Alation

JUNE 28, 2022

This is where metadata, or the data about data, comes into play. Having a data catalog is the cornerstone of your data governance strategy, but what supports your data catalog? Your metadata management framework provides the underlying structure that makes your data accessible and manageable.

Metadata 52

Metadata Management Data Governance Machine Learning 52

erwin

APRIL 29, 2020

These tools range from enterprise service bus (ESB) products, data integration tools; extract, transform and load (ETL) tools, procedural code, application program interfaces (API)s, file transfer protocol (FTP) processes, and even business intelligence (BI) reports that further aggregate and transform data.

Key Performance Indicator 111

Key Performance Indicator Metadata Data Governance Data Quality 111

Wayne Yaddow

MARCH 14, 2025

How dbt Core aids data teams test, validate, and monitor complex data transformations and conversions Photo by NASA on Unsplash Introduction dbt Core, an open-source framework for developing, testing, and documenting SQL-based data transformations, has become a must-have tool for modern data teams as the complexity of data pipelines grows.

Data Transformation 52

Data Transformation Testing Unstructured Data Data Quality 52

Wayne Yaddow

MARCH 5, 2025

The goal is to examine five major methods of verifying and validating data transformations in data pipelines with an eye toward high-quality data deployment. First, we look at how unit and integration tests uncover transformation errors at an early stage. Applicability by Transformation Type 2.

Testing 52

Testing Data Transformation Statistics Metadata 52

CIO Business Intelligence

AUGUST 3, 2023

“You had to be an expert in the programming language that interacts with that data, and understand the relationships of each data element within each data source, let alone understand its relation to elements in other data sources,” he says. Without those templates, it’s hard to add such information after the fact.”

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

Alation

OCTOBER 26, 2021

They need trusted data to drive reliable reporting, decision-making, and risk reduction. A Strong Data Culture Supports Strategic Decision Making. Our successful customers invest in and infuse data and analytics throughout the enterprise. After all, finance is one of the greatest consumers of data within a business.

Finance 52

Finance Data Transformation Enterprise Metrics 52

AWS Big Data

AUGUST 26, 2024

Duplicating data from a production database to a lower or lateral environment and masking personally identifiable information (PII) to comply with regulations enables development, testing, and reporting without impacting critical systems or exposing sensitive customer data. This saves time over manually defining schemas.

Visualization 115

Visualization Metadata Data Transformation Testing 115

AWS Big Data

NOVEMBER 15, 2023

It seamlessly consolidates data from various data sources within AWS, including AWS Cost Explorer (and forecasting with Cost Explorer ), AWS Trusted Advisor , and AWS Compute Optimizer. Data providers and consumers are the two fundamental users of a CDH dataset. You might notice that this differs slightly from traditional ETL.

Analytics 110

Analytics Dashboards Metadata Data Warehouse 110

erwin

MARCH 4, 2021

And when you talk about that question at a high level, he says, you get a very “simple answer,”– which is ‘the only thing we want to have is the right data with the right quality to the right person at the right time at the right cost.’. The Why: Data Governance Drivers. Why should companies care about data governance?

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. Data virtualization is ideal in any situation where the is necessary: Information coming from diverse data sources.

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

CIO Business Intelligence

FEBRUARY 20, 2024

Legacy data management is holding back manufacturing transformation Until now, however, this vision has remained out of reach. The data transformation imperative What Denso and other industry leaders realise is that for IT-OT convergence to be realised, and the benefits of AI unlocked, data transformation is vital.

Data Architecture 98

Data Architecture Unstructured Data Manufacturing IT 98

Octopai

NOVEMBER 23, 2020

In fact, the LIBOR transition program marks one of the largest data transformation obstacles ever seen in financial services. Building an inventory of what will be affected is a huge undertaking across all of the data, reports, and structures that must be accounted for. Automated Data Lineage for Your LIBOR Project.

Metadata 72

Metadata Enterprise Business Intelligence Data Governance 72

Cloudera

OCTOBER 7, 2022

dbt allows data teams to produce trusted data sets for reporting, ML modeling, and operational workflows using SQL, with a simple workflow that follows software engineering best practices like modularity, portability, and continuous integration/continuous development (CI/CD). The Open Data Lakehouse . Introduction.

Data Warehouse 81

Data Warehouse Data Transformation Machine Learning Data Lake 81

Octopai

NOVEMBER 13, 2022

The modern data stack is a data management system built out of cloud-based data systems. A given modern data stack will usually include components for data ingestion from your data sources, data transformation, data storage, data analysis and reporting.

Enterprise 97

Enterprise Data Warehouse Reporting Metadata 97

Cloudera

JUNE 30, 2022

These tools empower analysts and data scientists to easily collaborate on the same data, with their choice of tools and analytic engines. No more lock-in, unnecessary data transformations, or data movement across tools and clouds just to extract insights out of the data.

Data Lake 88

Data Lake Data Warehouse Data Architecture Metadata 88

Ontotext

NOVEMBER 18, 2021

OntoRefine is a data transformation tool that lets you unite plenty of data formats and get them into your triplestore. One of the core upsides of storing your data in that format is inference. You can think about that as metadata about the data, describing its relationships. Inferring new knowledge.

Visualization 98

Visualization Reporting Metadata Enterprise 98

Cloudera

OCTOBER 11, 2021

The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata. Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x.

Data Lake 95

Data Lake Cost-Benefit Data-driven Dashboards 95

AWS Big Data

DECEMBER 21, 2023

The data products used inside the company include insights from user journeys, operational reports, and marketing campaign results, among others. The data platform serves on average 60 thousand queries per day. The data volume is in double-digit TBs with steady growth as business and data sources evolve.

Data Lake 115

Data Lake Data Warehouse Data-driven B2B 115

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. A data store lets a business connect existing data with new data and discover new insights with real-time analytics and business intelligence. Increase trust in AI outcomes.

Risk 70

Risk Modeling Management Metadata 70

AWS Big Data

AUGUST 1, 2023

Although Jira Cloud provides reporting capability, loading this data into a data lake will facilitate enrichment with other business data, as well as support the use of business intelligence (BI) tools and artificial intelligence (AI) and machine learning (ML) applications. For InitialRunFlag , choose Setup.

Data Lake 98

Data Lake Data Transformation Data-driven Cost-Benefit 98

AWS Big Data

NOVEMBER 16, 2023

Data Vault 2.0 allows for the following: Agile data warehouse development Parallel data ingestion A scalable approach to handle multiple data sources even on the same entity A high level of automation Historization Full lineage support However, Data Vault 2.0

Enterprise 110

Enterprise Data Warehouse Data Lake Optimization 110

AWS Big Data

MARCH 9, 2023

Amazon QuickSight is a fully managed, cloud-native business intelligence (BI) service that makes it easy to connect to your data, create interactive dashboards and reports, and share these with tens of thousands of users, either within QuickSight or embedded in your application or website.

Slice and Dice 98

Slice and Dice Dashboards Analytics Interactive 98

Octopai

JANUARY 19, 2021

With Octopai’s support and analysis of Azure Data Factory, enterprises can now view complete end-to-end data lineage from Azure Data Factory all the way through to reporting for the first time ever.

Metadata 52

Metadata ROI Machine Learning Data Quality 52

Alation

APRIL 4, 2023

Now, joint users will get an enhanced view into cloud and data transformations , with valuable context to guide smarter usage. Integrating helpful metadata into user workflows gives all people, from data scientists to analysts , the context they need to use data more effectively.

Metadata 52

Metadata Cost-Benefit Data Transformation Predictive Modeling 52

AWS Big Data

MARCH 13, 2024

You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches. Athena is used to run geospatial queries on the location data stored in the S3 buckets. Choose Run.

Analytics 121

Analytics IoT Metadata Internet of Things 121

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 121

Data Lake Management Metrics Data Warehouse 121

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. Creating a High-Quality Data Pipeline.

Data Governance 40

Data Governance Risk Metadata Management 40

AWS Big Data

JULY 20, 2023

This data is then used by various applications for streaming analytics, business intelligence, and reporting. In addition, using Apache Iceberg’s metadata tables proved to be very helpful in identifying issues related to the physical layout of Iceberg’s tables, which can directly impact query performance.

Data Lake 98

Data Lake Analytics Snapshot Data Quality 98

Octopai

DECEMBER 11, 2022

It’s for that reason that even as the first BCBS-239 implementation deadline came into effect a few years ago, McKinsey reported that one-third of Global Systemically Important Banks had focused on “documenting data lineage up to the level of provisioning data elements and including data transformation.”.

Insurance 52

Insurance Risk Metadata Visualization 52

IBM Big Data Hub

MARCH 14, 2024

This involves unifying and sharing a single copy of data and metadata across IBM® watsonx.data ™, IBM® Db2 ®, IBM® Db2® Warehouse and IBM® Netezza ®, using native integrations and supporting open formats, all without the need for migration or recataloging. With Netezza support for 1.2

Cost-Benefit 75

Cost-Benefit Metadata Optimization Management 75

AWS Big Data

FEBRUARY 6, 2023

The task_id used can be the name of your choice; here we use add_steps : # EMR steps to be executed by EMR cluster SPARK_TEST_STEPS = [{ 'Name': 'Run Spark', 'ActionOnFailure': 'CANCEL_AND_WAIT', 'HadoopJarStep': { 'Jar': 'command-runner.jar', 'Args': ['spark-submit', '/home/hadoop/aggregations.py', 's3://{}/data/transformed/green'.format(S3_BUCKET_NAME),

Management 98

Management Interactive Publishing Metadata 98

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

Alation

JANUARY 17, 2023

These help data analysts visualize key insights that can help you make better data-backed decisions. ELT Data Transformation Tools: ELT data transformation tools are used to extract, load, and transform your data. Examples of data transformation tools include dbt and dataform.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 52

AWS Big Data

APRIL 25, 2024

Alternatively, you can use AWS Glue for Apache Spark, which provides built-in support for bucketing configurations during the data transformation process. AWS Glue allows you to define bucketing parameters, such as the number of buckets and the columns to bucket on, providing an optimized data layout for efficient querying with Athena.

Optimization 71

Optimization Data Lake Cost-Benefit Reporting 71