Jet Global

SEPTEMBER 22, 2023

In a rapidly evolving business environment, timely insights from data and the ability to react quickly to change are critical. Business intelligence is a key tool, empowering companies to get the most out of their data by providing tools to analyze information, streamline operations, track performance, and inform decision-making.

Visualization 52

Visualization Reporting Data Warehouse OLAP 52

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? #1

Metadata 54

Metadata Enterprise Management Data Warehouse 54

Jen Stirrup

MARCH 29, 2023

Put together, these factors help to provide the company with a competitive advantage since better data – and better use of data – leads to better strategies. Data as a product as well as a foundation The data foundation is critical for all types of reporting and analytics.

Metadata 120

Metadata Data Warehouse Data Integration Business Intelligence 120

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

CIO Business Intelligence

OCTOBER 13, 2023

Data architects are frequently part of a data science team and tasked with leading data system projects. They often report to data infrastructure and data science leads. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 131

Data Architecture Data Warehouse Statistics Visualization 131

erwin

JUNE 26, 2020

Given the value this sort of data-driven insight can provide, the reason organizations need a data catalog should become clearer. It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., Three Types of Metadata in a Data Catalog. Technical Metadata.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

DataKitchen

SEPTEMBER 21, 2023

Bridging the Gap: How ‘Data in Place’ and ‘Data in Use’ Define Complete Data Observability In a world where 97% of data engineers report burnout and crisis mode seems to be the default setting for data teams, a Zen-like calm feels like an unattainable dream. What is Data in Use?

Testing 176

Testing Data Quality Predictive Modeling Metrics 176

Jet Global

FEBRUARY 23, 2024

Data sources are crucial for reporting, analyzing, and acting on transactional and corporate data and connecting these sources in real time with various tools like connectors, ETL tools, mashups, Web services, and data source-neutral BI solutions is essential. Data warehouses can be complex, time-consuming, and expensive.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

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. Easy to report problems and receive updates on fixes.

Data Architecture 246

Data Architecture Data Lake Cost-Benefit Data Warehouse 246

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 97

Data Warehouse Data Lake Analytics Machine Learning 97

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. How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools.

Risk 78

Risk Modeling Management Metadata 78

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 85

Data Lake Data Warehouse B2B Data-driven 85

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 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

Cloudera

DECEMBER 10, 2020

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. Data warehouses have been broadly adopted to provide timely reports and valuable insights.

Data Warehouse 98

Data Warehouse Metadata Cost-Benefit Optimization 98

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. This tool examines all the data assets in your enterprise.

Metadata 52

Metadata Reporting Business Intelligence Data Warehouse 52

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 68

Analytics Data Warehouse Data Lake Metadata 68

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. Microsoft Excel is a phenomenal tool for ad hoc analysis and reporting.

Finance 78

Finance Data Warehouse OLAP Reporting 78

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

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 98

Data Lake Sales Data Warehouse Snapshot 98

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 91

Management Data Warehouse Metrics Dashboards 91

datapine

SEPTEMBER 29, 2022

In this article, we will detail everything which is at stake when we talk about DQM: why it is essential, how to measure data quality, the pillars of good quality management, and some data quality control techniques. But first, let’s define what data quality actually is. 2 – Data profiling. 4 – Data Reporting.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Jet Global

SEPTEMBER 19, 2023

In fact, a recent Gartner report on cloud expenditure found that cross-industry cloud spend has risen from 8% as a percentage of total IT spend in 2018 to 16% in 2022. Data Management How do we create a data warehouse or data lake in the cloud using our cloud ERP? How do we get the most out of our BI investment?

Cost-Benefit 52

Cost-Benefit Data Warehouse Reporting Enterprise 52

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 77

Enterprise Data Warehouse Reporting Metadata 77

AWS Big Data

MARCH 29, 2024

However, to analyze trends over time, aggregate from different dimensions, and share insights across the organization, a purpose-built business intelligence (BI) tool like Amazon QuickSight may be more effective for your business. With these insights, teams have the visibility to make data integration pipelines more efficient.

Metrics 101

Metrics Visualization Dashboards Interactive 101

IBM Big Data Hub

JANUARY 5, 2023

The right data architecture can help your organization improve data quality because it provides the framework that determines how data is collected, transported, stored, secured, used and shared for business intelligence and data science use cases.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 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.

Metadata 52

Metadata Data Warehouse Enterprise Business Intelligence 52

Octopai

FEBRUARY 27, 2020

Data sources are growing nonstop, and as soon as you think you have everything under control, more data new comes along and you’re back to square one, trying to figure out what caused a particular error in a report, for example. Why Spend Hours & Days on Data Mapping? Want to acquire better data insights?

Metadata 52

Metadata Data Warehouse Reporting Software 52

BI-Survey

FEBRUARY 23, 2023

Data knowledge is essential to data and analytics There is a clear understanding that data is an asset to the organization. Almost three quarters of respondents also state that they have recognized the need to invest in ways to access, link and understand metadata. These include tools for metadata management (e.g.,

Metadata 52

Metadata Data-driven Data Strategy Strategy 52

Octopai

AUGUST 3, 2020

You know it’s going to take you forever and it’s going to be extremely tedious as you’ve got to map out the data in your systems manually and try to figure out what needs to be migrated and what doesn’t. More specifically, you must establish a clear inventory of the data that your company processes.

Metadata 61

Metadata Reporting Data Warehouse Business Intelligence 61

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.

Interactive 87

Interactive Metadata Data Warehouse Data-driven 87

Octopai

JUNE 15, 2020

Business intelligence databases are dynamic repositories that must often be adjusted based on organizational and or regulatory requirements. To make changes to a system, report, or process, BI developers must first perform impact analysis in order to gauge the potential impact of making such a change on the rest of the environment.

Insurance 52

Insurance Metadata Business Intelligence Data Warehouse 52

Octopai

DECEMBER 10, 2019

Well, scoot over Templeton, because it’s also going to be the year of the Automated Business Glossary for business intelligence and data governance teams everywhere. Automated Business Glossary Tools Streamline Processes. Check out our eBook on Automated Business Glossaries to learn more.

Metadata 53

Metadata Data Warehouse Reporting Business Intelligence 53

erwin

APRIL 27, 2022

In data warehousing, the data is extracted and transported from production database(s) into a data warehouse for reporting and analysis. Change Data Capture identifies and processes only the data that has changed and stores the changed data in a form so as to be of further use.

Data Governance 52

Data Governance Digital Transformation Metadata Data Warehouse 52

BI-Survey

FEBRUARY 7, 2022

Creating all reports in a single tool and storing all data in a common data warehouse was meant to boost efficiency. Instead of curbing expenditure, horizontal integration curbed the innovative capacity of companies to use their data. And transparency is a must to democratize access to data in a company.

Analytics 52

Analytics Cost-Benefit Metadata Software 52

CIO Business Intelligence

NOVEMBER 22, 2022

External data sharing gets strategic Data sharing between business partners is becoming far easier and much more cooperative, observes Mike Bechtel, chief futurist at business advisory firm Deloitte Consulting. The fabric, especially at the active metadata level, is important, Saibene notes.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

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. Meaningful business context. Improved trust and confidence in data.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

FineReport

NOVEMBER 17, 2021

It was an American interactive data visualization software company of business intelligence. Tableau : There are specialized modules to manage metadata. FineReport: When organizing data management, we may face data source replacement. In SQL, the data source table name needs to be changed. FineReport.

KPI 52

KPI Dashboards Metadata Data Warehouse 52