Jet Global

JUNE 5, 2019

Data drives everything in the business world, from manufacturing to supply chain logistics to retail sales to customer experience to post-sale marketing and beyond, data holds the secrets to making processes more efficient, production costs cheaper, profit margins higher and marketing campaigns more effective.

Data mining 75

Data mining Business Intelligence OLAP Key Performance Indicator 75

Octopai

FEBRUARY 12, 2020

Like any good puzzle, metadata management comes with a lot of complex variables. That’s why you need to use data dictionary tools, which can help organize your metadata into an archive that can be navigated with ease and from which you can derive good information to power informed decision-making. Why Have a Data Dictionary?

Metadata 54

Metadata Enterprise Management Data Warehouse 54

AWS Big Data

MAY 7, 2024

Data governance is a key enabler for teams adopting a data-driven culture and operational model to drive innovation with data. Amazon DataZone allows you to simply and securely govern end-to-end data assets stored in your Amazon Redshift data warehouses or data lakes cataloged with the AWS Glue data catalog.

Metadata 78

Metadata Data Lake Data Processing Data-driven 78

Octopai

SEPTEMBER 10, 2020

Business Intelligence & Analytics: It’s a hard knock life for these guys. This is why a data lineage tool, namely an automated data lineage tool, is king for Business Intelligence teams. . Data lineage powers BI insights. Business Intelligence + data lineage helps companies win .

Business Intelligence 52

Business Intelligence Data Warehouse Dashboards Reporting 52

Jen Stirrup

MARCH 29, 2023

They are also starting to realize – and accept – that data is challenging. Post-COVID, companies now understand that IT skills are different from data skills. It is easier to list the symptoms of a problematic data foundation as they are often pretty clear to business users.

Metadata 121

Metadata Data Warehouse Data Integration Business Intelligence 121

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 104

Data Warehouse Data Lake Analytics Machine Learning 104

DataKitchen

AUGUST 3, 2021

The past decades of enterprise data platform architectures can be summarized in 69 words. First-generation – expensive, proprietary enterprise data warehouse and business intelligence platforms maintained by a specialized team drowning in technical debt. See the pattern? The problem is not “you.”

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

erwin

JUNE 26, 2020

If you’re serious about a data-driven strategy , you’re going to need a data catalog. Organizations need a data catalog because it enables them to create a seamless way for employees to access and consume data and business assets in an organized manner. Three Types of Metadata in a Data Catalog.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

CIO Business Intelligence

MAY 24, 2022

Just after launching a focused data management platform for retail customers in March, enterprise data management vendor Informatica has now released two more industry-specific versions of its Intelligent Data Management Cloud (IDMC) — one for financial services, and the other for health and life sciences.

Finance 131

Finance Management Metadata Data Quality 131

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. Iceberg stores the metadata pointer for all the metadata files.

Data Lake 97

Data Lake Data Warehouse Metadata Data Architecture 97

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 80

Data Warehouse Cost-Benefit Metadata Data-driven 80

Cloudera

DECEMBER 10, 2020

Why worry about costs with cloud-native data warehousing? Have you been burned by the unexpected costs of a cloud data warehouse? If not, before adopting a cloud data warehouse, consider the true costs of a cloud-native data warehouse. These costs impede the adoption of cloud-native data warehouses.

Data Warehouse 98

Data Warehouse Metadata Cost-Benefit Optimization 98

AWS Big Data

DECEMBER 5, 2023

This frees up our local computer space, greatly automates the survey cleaning and analysis step, and allows our clients to easily access the data results. .” — Harman Singh Dhodi, Analyst at HR&A Advisors, Inc. The first step in this process is mapping the digital divide.

Measurement 85

Measurement Dashboards Data Warehouse Analytics 85

CIO Business Intelligence

OCTOBER 13, 2023

Data architecture is a complex and varied field and different organizations and industries have unique needs when it comes to their data architects. Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes.

Data Architecture 127

Data Architecture Data Warehouse Statistics Visualization 127

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 83

Data Lake Data Warehouse Machine Learning Cost-Benefit 83

Alation

FEBRUARY 7, 2023

The product collected an impressive amount of metadata, from the user interface to the database structure. It then translated all that metadata into an image resembling a spider’s web. That was my earliest taste of data lineage. They sought documentation to help them locate the source of the data from the warehouse.

Metadata 52

Metadata Data Warehouse Visualization Data Quality 52

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 90

Data Lake Data Warehouse Machine Learning Cost-Benefit 90

CIO Business Intelligence

SEPTEMBER 6, 2022

When Steve Pimblett joined The Very Group in October 2020 as chief data officer, reporting to the conglomerate’s CIO, his task was to help the enterprise uncover value in its rich data heritage. There was no one to help everybody with standards and central approaches, so every business vertical was doing it differently,” he says. “‘It’

IT 81

IT Forecasting Data Lake Enterprise 81

Ontotext

AUGUST 4, 2023

A data fabric utilizes an integrated data layer over existing, discoverable, and inferenced metadata assets to support the design, deployment, and utilization of data across enterprises, including hybrid and multi-cloud platforms. It also helps capture and connect data based on business or domains.

Metadata 52

Metadata Data-driven Data Architecture Data Quality 52

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 87

Enterprise Data Warehouse Snapshot Cost-Benefit 87

AWS Big Data

FEBRUARY 21, 2023

Data warehouses play a vital role in healthcare decision-making and serve as a repository of historical data. A healthcare data warehouse can be a single source of truth for clinical quality control systems. This is one of the biggest hurdles with the data vault approach. What is a dimensional data model?

Data Warehouse 66

Data Warehouse Data Lake Cost-Benefit Modeling 66

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. A data hub contains data at multiple levels of granularity and is often not integrated.

Analytics 73

Analytics Data Warehouse Data Lake Metadata 73

IBM Big Data Hub

OCTOBER 16, 2023

Artificial intelligence (AI) adoption is still in its early stages. 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. ” Are foundation models trustworthy?

Risk 75

Risk Modeling Management Metadata 75

AWS Big Data

DECEMBER 21, 2023

The data volume is in double-digit TBs with steady growth as business and data sources evolve. smava’s Data Platform team faced the challenge to deliver data to stakeholders with different SLAs, while maintaining the flexibility to scale up and down while staying cost-efficient. This is the Data Mart stage.

Data Lake 93

Data Lake Data Warehouse Data-driven B2B 93

AWS Big Data

NOVEMBER 29, 2023

Customizing foundation models The need for data is quite obvious if you are building your own foundation models (FMs). These models need vast amounts of data. But data is necessary even when you are building on top of FMs. Customers have created hundreds of thousands of data lakes on Amazon S3.

Data Warehouse 111

Data Warehouse Data Lake Data Integration Dashboards 111

IBM Big Data Hub

JANUARY 5, 2023

But there’s another factor of data quality that doesn’t get the recognition it deserves: your data architecture. How the right data architecture improves data quality. Next generation of big data platforms and long running batch jobs operated by a central team of data engineers have often led to data lake swamps.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

AWS Big Data

APRIL 28, 2023

Amazon Redshift is a fast, scalable, secure, and fully managed cloud data warehouse that makes it simple and cost-effective to analyze all your data using standard SQL and your existing ETL (extract, transform, and load), business intelligence (BI), and reporting tools. In this post, we use IAM credentials.

Interactive 95

Interactive Metadata Data Warehouse Data-driven 95

Octopai

MARCH 24, 2020

Business Intelligence has a lot depending on it. Every time someone from Marketing or Sales or HR needs a report created or modified, or every time there’s a problem with some data in a report that needs to be sorted ASAP – who do you call? So, what is BI Intelligence you ask? Business Glossary.

Metadata 43

Metadata Cost-Benefit Business Intelligence ROI 43

AWS Big Data

SEPTEMBER 25, 2023

With Amazon Redshift , you can run a complex mix of workloads on your data warehouse, such as frequent data loads running alongside business-critical dashboard queries and complex transformation jobs. We also see more and more data science and machine learning (ML) workloads.

Management 99

Management Data Warehouse Metrics Dashboards 99

Octopai

MAY 18, 2020

The finance team is behind on the year-end accounting, and it’s shutting the window you have to generate business review materials. Finally, the accounting close is completed and the data is loaded to the data warehouse from which you generate the reports. Automated data discovery is the key to BI metadata management.

Metadata 52

Metadata Reporting Business Intelligence Data Warehouse 52

Octopai

OCTOBER 20, 2021

Octopai, the leader in automated data lineage, data catalog and data discovery, announced today its support and analysis of Amazon Redshift, one of the fastest and most widely used cloud data warehouses. By getting the full picture of what and how different tables, columns etc.

Metadata 52

Metadata Data Warehouse Enterprise Business Intelligence 52

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 107

Data Lake Management Metrics Data Warehouse 107

AWS Big Data

MARCH 10, 2023

However, as data processing at scale solutions grow, organizations need to build more and more features on top of their data lakes. They enable transactions on top of data lakes and can simplify data storage, management, ingestion, and processing. The Iceberg table is synced with the AWS Glue Data Catalog.

Data Lake 107

Data Lake Sales Data Warehouse Snapshot 107

datapine

MAY 29, 2019

BI architecture has emerged to meet those requirements, with data warehousing as the backbone of these processes. One of the BI architecture components is data warehousing. What Is Data Warehousing And Business Intelligence? BI Architecture Framework In Modern Business. Data integration. Data storage.

Business Intelligence 196

Business Intelligence Data Warehouse Dashboards Visualization 196

CIO Business Intelligence

NOVEMBER 22, 2022

Every enterprise needs a data strategy that clearly defines the technologies, processes, people, and rules needed to safely and securely manage its information assets and practices. Here’s a quick rundown of seven major trends that will likely reshape your organization’s current data strategy in the days and months ahead.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

Jet Global

DECEMBER 1, 2020

Finance teams often work with business intelligence (BI) tools to analyze data, identify trends, pinpoint discrepancies, and build informative, compelling reports for management. In addition, it can be very helpful to have a metadata layer in place that can help non-developers make sense of the information in the database.

Finance 78

Finance Data Warehouse OLAP Reporting 78

datapine

SEPTEMBER 29, 2022

What Is Data Quality Management (DQM)? Data quality management is a set of practices that aim at maintaining a high quality of information. It goes all the way from the acquisition of data and the implementation of advanced data processes, to an effective distribution of data.

Data Quality 241

Data Quality Metrics Data-driven Management 241