Octopai

APRIL 19, 2021

Without organized metadata management, the validity of a company’s data is compromised and they won’t achieve adequate compliance, data governance, or generate correct insights. Additionally, the BI team will have trouble pinpointing the cause of errors, leading to inaccurate reports. TDWI – Dave Stodder.

Metadata 52

Metadata Management Business Intelligence Data Governance 52

erwin

DECEMBER 12, 2019

As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all. Quicker Project Delivery: Accelerate Big Data deployments, Data Vaults, data warehouse modernization, cloud migration, etc., Click here to get a free copy of the report. by up to 70 percent.

Metadata 84

Metadata Data Governance Digital Transformation Data Quality 84

Jedox

OCTOBER 22, 2020

Other challenges to data analytics include data storage, data quality, and a lack of knowledge and tools necessary to make sense of the data and generate those critical insights. Limited self-service reporting across the enterprise. Self-service reporting. Exception reporting.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

CIO Business Intelligence

AUGUST 9, 2022

Data engineers are often responsible for building algorithms for accessing raw data, but to do this, they need to understand a company’s or client’s objectives, as aligning data strategies with business goals is important, especially when large and complex datasets and databases are involved. Data engineer salary.

Analytics 123

Analytics Data Science Statistics Unstructured Data 123

erwin

DECEMBER 12, 2019

As data continues to proliferate, so does the need for data and analytics initiatives to make sense of it all. Quicker Project Delivery: Accelerate Big Data deployments, Data Vaults, data warehouse modernization, cloud migration, etc., Click here to get a free copy of the report. by up to 70 percent.

Metadata 52

Metadata Data Governance Digital Transformation Data Quality 52

Sisense

SEPTEMBER 3, 2020

They are the link between the data resources available to an enterprise and executives looking for opportunities to make the business better, faster, and stronger. Data Analyst. Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization.

Statistics 97

Statistics Metrics Visualization Finance 97

CIO Business Intelligence

JANUARY 30, 2024

Corporate ESG reporting is getting real for companies around the globe. Enacted and proposed regulations in the EU, US, and beyond are deepening reporting requirements in an effort to change business behavior. The foundation for ESG reporting, of course, is data.

Reporting 102

Reporting Data Quality Strategy Data-driven 102

CIO Business Intelligence

APRIL 29, 2022

The data-first transformation journey can appear to be a lengthy one, but it’s possible to break it down into steps that are easier to digest and can help speed you along the pathway to achieving a modern, data-first organization. Key features of data-first leaders. 5x more likely to be highly resilient in terms of data loss.

Digital Transformation 115

Digital Transformation Strategy Data-driven Data Strategy 115

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. Data quality Data quality is essentially the measure of data integrity.

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

Peter James Thomas

AUGUST 18, 2018

Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation. Of course some architectures featured both paradigms as well. This required additional investments in metadata.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

CIO Business Intelligence

FEBRUARY 20, 2023

To earn this cert, candidates should know how to maintain and modify Sales Cloud and Service Cloud applications; manage users, data, and security; and construct dashboards, reports, and workflows. The certification emphasizes testing, governance, and integration with external systems within an organization’s infrastructure.

Consulting 60

Consulting B2B Cost-Benefit Sales 60

DataKitchen

OCTOBER 11, 2021

First, you must understand the existing challenges of the data team, including the data architecture and end-to-end toolchain. The delays impact delivery of the reports to senior management, who are responsible for making business decisions based on the dashboard. Second, you must establish a definition of “done.”

Testing 152

Testing Metadata Dashboards Statistics 152

CIO Business Intelligence

MARCH 9, 2022

They conveniently store data in a flat architecture that can be queried in aggregate and offer the speed and lower cost required for big data analytics. On the other hand, they don’t support transactions or enforce data quality. Each ETL step risks introducing failures or bugs that reduce data quality. .

Data Lake 103

Data Lake Unstructured Data Data Warehouse Data Quality 103

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 Poor data quality.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

Peter James Thomas

MAY 3, 2019

Collation of Data to provide Information. This area includes what is often described as “traditional” reporting [3] , Dashboards and analysis facilities. The bulk of Business Intelligence efforts would also fall into this area, but there is some overlap with the area I next describe as well.

Strategy 55

Strategy Data Architecture Data Quality Data Strategy 55

CIO Business Intelligence

FEBRUARY 28, 2024

Even in its infancy, gen AI has become an accepted course of action and application, and the most common use cases include automation of IT processes, security and threat detection, supply chain intelligence, and automating customer service and network processes, according to a report released by IBM in January.

IT 113

IT Consulting Modeling Enterprise 113

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. Prior to the creation of the data lake, Orca’s data was distributed among various data silos, each owned by a different team with its own data pipelines and technology stack.

Data Lake 88

Data Lake Analytics Snapshot Optimization 88

CIO Business Intelligence

JULY 28, 2023

At the same time, it reduces risk by ensuring that all data is under control, avoiding inconsistencies, and adhering to a single source of truth. In a recent IDC Infobrief , more than half of respondents report that regulatory compliance is a primary factor in deciding how and where they store enterprise data.

Risk 79

Risk Management Cost-Benefit Data mining 79

Peter James Thomas

AUGUST 2, 2019

Business Glossary (contributor: Tenny Thomas Soman ). Data Architecture – Definition (2). Data Catalogue. Data Community. Data Domain (contributor: Taru Väre ). Data Enrichment. Data Federation. Data Function. Data Model. Data Operating Model. Chart (Graph).

Analytics 69

Analytics Data Analytics Data Architecture Statistics 69

CIO Business Intelligence

NOVEMBER 7, 2023

But what exactly is involved in breaking down data silos? Centralized reporting boosts data value For more than a decade, pediatric health system Phoenix Children’s has operated a data warehouse containing more than 120 separate data systems, providing the ability to connect data from disparate systems.

Data Warehouse 139

Data Warehouse Digital Transformation Data-driven Reporting 139

IBM Big Data Hub

AUGUST 4, 2023

Today, the way businesses use data is much more fluid; data literate employees use data across hundreds of apps, analyze data for better decision-making, and access data from numerous locations. This results in more marketable AI-driven products and greater accountability.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

BI-Survey

FEBRUARY 6, 2020

Modernizing and optimizing enterprise reporting – or classical BI – has not been such a priority for many of today’s organizations, even though it constitutes the backbone of information supply for decision support. Technological innovations and their increasing proliferation are shaping enterprise reporting and BI.

Reporting 59

Reporting Optimization Enterprise Data Quality 59

CIO Business Intelligence

JANUARY 20, 2023

In particular, companies that were leaders at using data and analytics had three times higher improvement in revenues, were nearly three times more likely to report shorter times to market for new products and services, and were over twice as likely to report improvement in customer satisfaction, profits, and operational efficiency.

Data Lake 125

Data Lake Data-driven Finance Data Architecture 125

Alation

OCTOBER 12, 2021

In enterprises especially, which typically collect vast amounts of data, analysts often struggle to find, understand, and trust data for analytics reporting. Immense volume leads to data silos, and a holistic view of the business becomes more difficult to achieve. Evaluate and monitor data quality.

Strategy 52

Strategy Enterprise Analytics Data Governance 52

AWS Big Data

APRIL 5, 2023

The company decided to use AWS to unify its business intelligence (BI) and reporting strategy for both internal organization-wide use cases and in-product embedded analytics targeted at its customers. In this post, we share how Showpad used QuickSight to streamline data and insights access across teams and customers.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52