CIO Business Intelligence

OCTOBER 26, 2023

Business intelligence (BI) analysts transform data into insights that drive business value. This is done by mining complex data using BI software and tools , comparing data to competitors and industry trends, and creating visualizations that communicate findings to others in the organization.

Business Intelligence 126

Business Intelligence Data-driven Statistics Data Warehouse 126

IBM Big Data Hub

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

AWS Big Data

MARCH 10, 2023

Since the deluge of big data over a decade ago, many organizations have learned to build applications to process and analyze petabytes of data. Data lakes have served as a central repository to store structured and unstructured data at any scale and in various formats.

Data Lake 102

Data Lake Sales Data Warehouse Snapshot 102

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 83

Enterprise Data Warehouse Snapshot Cost-Benefit 83

AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

IBM Big Data Hub

OCTOBER 16, 2023

As more businesses use AI systems and the technology continues to mature and change, improper use could expose a company to significant financial, operational, regulatory and reputational risks. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits.

Risk 77

Risk Modeling Management Metadata 77

datapine

SEPTEMBER 29, 2022

Today most of a company’s operations and strategic decisions heavily rely on data, so the importance of quality is even higher. And indeed, low-quality data is the leading cause of failure for advanced data and technology initiatives, to the tune of $9.7 2 – Data profiling. 1 – The people.

Data Quality 241

Data Quality Metrics Data-driven Management 241

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

IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. Technical metadata to describe schemas, indexes and other database objects.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

In(tegrate) the Clouds

DECEMBER 21, 2015

I enjoy the end of the year technology predictions, even though it’s hard to argue with this tweet from Merv Adrian: By 2016, 99% of readers will be utterly sick of predictions. 2016 will be the year of the data lake. I can’t help it. Merv Adrian (@merv) December 19, 2015. platform.twitter.com/widgets.js.

Technology 45

Technology Internet of Things Digital Transformation Software 45

Alation

JULY 22, 2021

This course called on the students to utilize the catalog to find and query sample data, and then to publish results into articles on the site. For the course, ‘Big Data and Society’, we loaded publicly available COVID-19 data into the catalog for student use and investigation. iSchool Skills for Data Catalog Management.

Informatics 98

Informatics Big Data Insurance Metadata 98

AWS Big Data

NOVEMBER 29, 2023

As part of the Talent Intelligence Platform Eightfold also exposes a data hub where each customer can access their Amazon Redshift-based data warehouse and perform ad hoc queries as well as schedule queries for reporting and data export. Securing customer data is a top priority for Eightfold.

Metadata 103

Metadata Data Warehouse Analytics Data Analytics 103

AWS Big Data

JULY 20, 2023

Apache Hive is a SQL-based data warehouse system for processing highly distributed datasets on the Apache Hadoop platform. The Hive metastore is a repository of metadata about the SQL tables, such as database names, table names, schema, serialization and deserialization information, data location, and partition details of each table.

Data Lake 77

Data Lake Metadata Data Processing Big Data 77

AWS Big Data

APRIL 8, 2024

Prior to this integration, you had to complete the following steps before Amazon DataZone could treat the published Data Catalog table as a managed asset: Identity the Amazon S3 location associated with Data Catalog table. Publish the table metadata to the Amazon DataZone business data catalog.

Finance 76

Finance Sales Publishing Metadata 76

erwin

APRIL 2, 2021

And knowing the business purpose translates into actively governing personal data against potential privacy and security violations. Do You Know Where Your Sensitive Data Is? Data is a valuable asset used to operate, manage and grow a business. Minimizing Risk Exposure with Data Intelligence.

Data Governance 106

Data Governance Cost-Benefit Risk Metadata 106

Alation

FEBRUARY 13, 2020

Why do we need a data catalog? What does a data catalog do? These are all good questions and a logical place to start your data cataloging journey. Data catalogs have become the standard for metadata management in the age of big data and self-service analytics. What is a Data Catalog?

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

erwin

MARCH 8, 2019

GDPR) and to ensure peak business performance, organizations often bring consultants on board to help take stock of their data assets. This sort of data governance “stock check” is important but can be arduous without the right approach and technology. That’s where data governance comes in ….

Data Governance 65

Data Governance Metadata Data Warehouse Data Quality 65

AWS Big Data

JANUARY 31, 2023

We have collected some of the key talks and solutions on data governance, data mesh, and modern data architecture published and presented in AWS re:Invent 2022, and a few data lake solutions built by customers and AWS Partners for easy reference. He comes from a background in machine learning and data lake architectures.

Data Lake 79

Data Lake Data Governance Data Architecture Data Warehouse 79

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation. This required additional investments in metadata. In Closing.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

Cloudera

FEBRUARY 11, 2019

“Disruption slows as cloud and nonrelational technology take their place beside traditional approaches , the leaders extend their lead, and distributed data approaches solidify their place as a best practice for DMSA.” Established, mature technologies represent an integral part of DMSA.

Management 42

Management Metadata Analytics Machine Learning 42

IBM Big Data Hub

JUNE 8, 2022

A typical organization’s data landscape consists of a large number of data stores across workflows, business processes and business units, including but not limited to data warehouses, data marts, data lakes, ODS, cloud data stores, and CRM databases. The volume of data assets.

Data-driven 58

Data-driven Enterprise Data Governance Data Lake 58

TDAN

MARCH 19, 2019

Various databases, plus one or more data warehouses, have been the state-of-the art data management infrastructure in companies for years. The emergence of various new concepts, technologies, and applications such as Hadoop, Tableau, R, Power BI, or Data Lakes indicate that changes are under way.

Management 84

Management Data Lake Data Warehouse Analytics 84

erwin

FEBRUARY 19, 2021

Metadata management is key to wringing all the value possible from data assets. However, most organizations don’t use all the data at their disposal to reach deeper conclusions about how to drive revenue, achieve regulatory compliance or accomplish other strategic objectives. What Is Metadata? Harvest data.

Metadata 110

Metadata Management Data Quality Cost-Benefit 110

AWS Big Data

FEBRUARY 24, 2023

An AWS Glue streaming job is connected to Kinesis Data Streams to process the data using the Iceberg connector. Athena uses the AWS Glue Data Catalog to store and retrieve table metadata for the Amazon S3 data in Iceberg format. To create your data warehouse or data lake, you must catalog this data.

Data Lake 80

Data Lake Metadata Testing Data Warehouse 80

Sisense

MAY 28, 2020

“Not only do they have to deal with data that is distributed across on-premises, hybrid, and multi-cloud environments, but they have to contend with structured, semi-structured, and unstructured data types. All of this results in a lot of friction within data-driven organizations. Creating a path to success.

Internet of Things 83

Internet of Things Metadata Data-driven Unstructured Data 83

Domino Data Lab

APRIL 3, 2019

It includes perspectives about current issues, themes, vendors, and products for data governance. My interest in data governance (DG) began with the recent industry surveys by O’Reilly Media about enterprise adoption of “ABC” (AI, Big Data, Cloud). Most of the data management moved to back-end servers, e.g., databases.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

AWS Big Data

MARCH 25, 2024

Streaming jobs constantly ingest new data to synchronize across systems and can perform enrichment, transformations, joins, and aggregations across windows of time more efficiently. Studio notebooks seamlessly combine these technologies to make advanced analytics on data streams accessible to developers of all skill sets.

Data Lake 90

Data Lake Unstructured Data Management Modeling 90

AWS Big Data

AUGUST 31, 2023

Amazon Redshift is a fast, fully managed petabyte-scale cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing business intelligence (BI) tools. Amazon Redshift also supports querying nested data with complex data types such as struct, array, and map.

Data Lake 92

Data Lake Data Warehouse Metadata Data Architecture 92

AWS Big Data

OCTOBER 4, 2023

An Amazon DataZone domain contains an associated business data catalog for search and discovery, a set of metadata definitions to decorate the data assets that are used for discovery purposes, and data projects with integrated analytics and ML tools for users and groups to consume and publish data assets.

Metadata 100

Metadata Data Lake Publishing Data Governance 100

AWS Big Data

JUNE 6, 2023

SumUp is a leading global financial technology company driven by the purpose of leveling the playing field for small businesses. Unless, of course, the rest of their data also resides in the Google Cloud. AWS Glue gave us a cost-efficient option to migrate the data and we further optimized storage cost by pruning cold data.

Analytics 56

Analytics Data Lake Testing Optimization 56

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

AWS Big Data

NOVEMBER 22, 2023

Apache Hudi is an open table format that brings database and data warehouse capabilities to data lakes. Apache Hudi helps data engineers manage complex challenges, such as managing continuously evolving datasets with transactions while maintaining query performance. He works based in Tokyo, Japan.

Data Lake 92

Data Lake Snapshot Metadata Optimization 92

AWS Big Data

APRIL 6, 2023

We realized we needed a data warehouse to cater to all of these consumer requirements, so we evaluated Amazon Redshift. At the same time, we had to find a way to implement entitlements in our Amazon Redshift data warehouse with the same set of tags that we had already defined in Lake Formation.

Data Warehouse 82

Data Warehouse Data Lake Management Data-driven 82

AWS Big Data

NOVEMBER 29, 2023

In 2013, Amazon Web Services revolutionized the data warehousing industry by launching Amazon Redshift , the first fully-managed, petabyte-scale, enterprise-grade cloud data warehouse. Amazon Redshift made it simple and cost-effective to efficiently analyze large volumes of data using existing business intelligence tools.

Data Warehouse 100

Data Warehouse Data Lake Analytics Machine Learning 100

Alation

JANUARY 17, 2023

It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Data orchestration tools. In the past, data movement was defined by ETL: extract, transform, and load.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

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.

Dashboards 94

Dashboards Analytics Metadata Data Warehouse 94

IBM Big Data Hub

JANUARY 18, 2023

They defined it as : “ A data lakehouse is a new, open data management architecture that combines the flexibility, cost-efficiency, and scale of data lakes with the data management and ACID transactions of data warehouses, enabling business intelligence (BI) and machine learning (ML) on all data. ”.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52