CIO Business Intelligence

MARCH 6, 2024

This was a gift because it forced us into data governance and we sell data governance products, so this wasn’t a new concept to us. The definition of ARR, for example, required debate between the CFO and the CEO, and then my team built the definition into the data warehouse. What’s the calculation?

Modeling 116

Modeling Management IT Metrics 116

Data Science 101

DECEMBER 3, 2019

Do you have a data governance document? What data do you collect? Technical Questions Before Starting a Data Strategy. How and where is your current data stored? Do you have a Business Intelligence (BI) tool? What is the current data infrastructure? Do you have a data warehouse?

Data Strategy 84

Data Strategy Strategy Data Warehouse Dashboards 84

CIO Business Intelligence

NOVEMBER 28, 2023

Still, to truly create lasting value with data, organizations must develop data management mastery. This means excelling in the under-the-radar disciplines of data architecture and data governance. The knock-on impact of this lack of analyst coverage is a paucity of data about monies being spent on data management.

Management 131

Management Data Architecture Data Lake Data Strategy 131

AWS Big Data

MARCH 7, 2023

Analytics reference architecture for gaming organizations In this section, we discuss how gaming organizations can use a data hub architecture to address the analytical needs of an enterprise, which requires the same data at multiple levels of granularity and different formats, and is standardized for faster consumption.

Analytics 71

Analytics Data Warehouse Data Lake Metadata 71

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 94

Management Data Warehouse Metrics Dashboards 94

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

erwin

APRIL 27, 2022

Best Data Governance Solution (erwin Data Intelligence). Best Data Modeling Solution (erwin Data Modeler). Best Data Security Solution (Quest ApexSQL). In data warehousing, the data is extracted and transported from production database(s) into a data warehouse for reporting and analysis.

Data Governance 52

Data Governance Digital Transformation Metadata Data Warehouse 52

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

Jet Global

FEBRUARY 5, 2019

Data is often imperfect and incomplete, but with smart data management, effective data governance, and centralized data storage, you can be well on your way to becoming a fully data-driven enterprise. . Reduce the Risk of Bad Data with Master Data Management (MDM). Download Now.

Data Quality 69

Data Quality Data Warehouse Business Intelligence Data Governance 69

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

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. Dimension-based models have been used extensively to build data warehouses.

Data Lake 102

Data Lake Sales Data Warehouse Snapshot 102

IBM Big Data Hub

DECEMBER 16, 2022

It uses metadata and data management tools to organize all data assets within your organization. It synthesizes the information across your data ecosystem—from data lakes, data warehouses, and other data repositories—to empower authorized users to search for and access business-ready data for their projects and initiatives.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

TDAN

MAY 31, 2022

As we enter a new cloud-first era, advancements in technology have helped companies capture and capitalize on data as much as possible. Deciding between which cloud architecture to use has always been a debate between two options: data warehouses and data lakes.

Data Lake 52

Data Lake Data Warehouse Technology Data Architecture 52

erwin

JUNE 26, 2020

It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., legacy systems, data warehouses, flat files stored on individual desktops and laptops, and modern, cloud-based repositories.).

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

CIO Business Intelligence

OCTOBER 13, 2022

Such an approach ensures that app modernization efforts meet any relevant certification requirements and solve business-specific problems. The airline also sought to provide analysts with finer data access controls so they could be more analytical and creative when driving revenue management decisions.

Insurance 115

Insurance Data Warehouse Manufacturing Forecasting 115

Jet Global

JULY 2, 2019

The sheer scale of data being captured by the modern enterprise has necessitated a monumental shift in how that data is stored. From the humble database through to data warehouses , data stores have grown both in scale and complexity to keep pace with the businesses they serve, and the data analysis now required to remain competitive.

Data Lake 73

Data Lake Data Warehouse Big Data Machine Learning 73

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. According to the Chinese Zodiac, 2020 is the year of the rat.

Metadata 53

Metadata Data Warehouse Reporting Business Intelligence 53

erwin

DECEMBER 12, 2019

Metadata is an important part of data governance, and as a result, most nascent data governance programs are rife with project plans for assessing and documenting metadata. But in many scenarios, it seems that the underlying driver of metadata collection projects is that it’s just something you do for data governance.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

BizAcuity

APRIL 1, 2023

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. However, many businesses seem to face a lot of challenges, which includes ensuring a ‘single source of truth’ across the organization.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

CIO Business Intelligence

MAY 28, 2022

In addition, the company has added new governance capabilities to IDMC on Azure, to allow users to apply management and security rules to the flow of data from disparate sources to Microsoft’s Power BI analytics software.

Management 105

Management Data Warehouse Software Strategy 105

CIO Business Intelligence

MAY 27, 2022

In addition, the company has added new governance capabilities to IDMC on Azure, to allow users to apply management and security rules to the flow of data from disparate sources to Microsoft’s Power BI analytics software.

Management 105

Management Data Warehouse Software Strategy 105

BizAcuity

JANUARY 31, 2023

Thanks to the recent technological innovations and circumstances to their rapid adoption, having a data warehouse has become quite common in various enterprises across sectors. However, many businesses seem to face a lot of challenges, which includes ensuring a ‘single source of truth’ across the organization.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

erwin

FEBRUARY 21, 2019

says retailers need to achieve a level of what he calls “data intelligence.” Given all of the data that flows into the modern retailer, this level of data intelligence requires a holistic, mature and well-planned data governance strategy.

Digital Transformation 69

Digital Transformation Risk Data Governance Sales 69

datapine

SEPTEMBER 29, 2022

With quality data at their disposal, organizations can form data warehouses for the purposes of examining trends and establishing future-facing strategies. Industry-wide, the positive ROI on quality data is well understood. The program manager should lead the vision for quality data and ROI.

Data Quality 241

Data Quality Metrics Data-driven Management 241

Alation

MAY 24, 2022

generally available on May 24, Alation introduces the Open Data Quality Initiative for the modern data stack, giving customers the freedom to choose the data quality vendor that’s best for them with the added confidence that those tools will integrate seamlessly with Alation’s Data Catalog and Data Governance application.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

Alation

DECEMBER 21, 2022

Transactional systems and data warehouses can then use the golden records as the entity’s most current, trusted representation. Data Catalog and Master Data Management. Early on, analysts used data catalogs to find and understand data more quickly.

Management 52

Management Data Quality Metadata Testing 52

CIO Business Intelligence

JUNE 14, 2023

CDP Data Analyst The Cloudera Data Platform (CDP) Data Analyst certification verifies the Cloudera skills and knowledge required for data analysts using CDP. Candidates show facility with data concepts and environments; data mining; data analysis; data governance, quality, and controls; and visualization.

Big Data 126

Big Data Data Analytics Analytics Predictive Modeling 126

FineReport

MAY 31, 2023

Furthermore, we will introduce some business intelligence solution that excels in simplifying the process of creating and utilizing a financial dashboard effectively. Finance and accounting teams often deal with data residing in multiple systems, such as accounting software, ERP systems, spreadsheets, and data warehouses.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

Cloudera

SEPTEMBER 23, 2022

These operations are part of the service and a key feature that drives lower total cost of ownership — you do not have to hire or staff an operations team to manage the data lakehouse. Your data warehouse dashboards might be running during business hours and remain unused during other hours.

Data Governance 103

Data Governance Strategy Enterprise Cost-Benefit 103

Octopai

FEBRUARY 12, 2020

. – Text descriptions of data objects that allow for greater interpretation and application of data than a basic label. Having a data dictionary means any potential user will be able to understand the data in a data warehouse. Streamline Your Enterprise Metadata and More Ways to Get Organized.

Metadata 54

Metadata Enterprise Management Data Warehouse 54

Jet Global

JANUARY 17, 2019

In today’s data-driven world, business intelligence (BI) and analytics play a huge role in better understanding your customers, improving your operations, and making actionable business decisions. Take a look at the data you need to use in order to get any value from business intelligence and analytics.

Business Intelligence 75

Business Intelligence Management Data Warehouse Data Governance 75

Domino Data Lab

APRIL 3, 2019

Paco Nathan ‘s latest column dives into data governance. This month’s article features updates from one of the early data conferences of the year, Strata Data Conference – which was held just last week in San Francisco. In particular, here’s my Strata SF talk “Overview of Data Governance” presented in article form.

Data Governance 84

Data Governance Machine Learning Metadata Big Data 84

BI-Survey

AUGUST 21, 2020

But what are the right measures to make the data warehouse and BI fit for the future? Can the basic nature of the data be proactively improved? The following insights came from a global BARC survey into the current status of data warehouse modernization. What role do technology and IT infrastructure play?

Data Warehouse 98

Data Warehouse Data Lake Data Governance Data Architecture 98

CIO Business Intelligence

DECEMBER 21, 2022

Every day, organizations of every description are deluged with data from a variety of sources, and attempting to make sense of it all can be overwhelming. So a strong business intelligence (BI) strategy can help organize the flow and ensure business users have access to actionable business insights. “By

IT 131

IT Business Intelligence Sales Key Performance Indicator 131

BI-Survey

FEBRUARY 17, 2020

From operational systems to support “smart processes”, to the data warehouse for enterprise management, to exploring new use cases through advanced analytics : all of these environments incorporate disparate systems, each containing data fragments optimized for their own specific task. .

Data Governance 89

Data Governance Data Warehouse Data Quality Data Strategy 89

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. Business intelligence (BI) platforms. Better Data Culture.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

Domino Data Lab

JULY 22, 2019

data science’s emergence as an interdisciplinary field – from industry, not academia. why data governance, in the context of machine learning is no longer a “dry topic” and how the WSJ’s “global reckoning on data governance” is potentially connected to “premiums on leveraging data science teams for novel business cases”.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109