Jet Global

FEBRUARY 25, 2025

Data cleansing is the process of identifying and correcting errors, inconsistencies, and inaccuracies in a dataset to ensure its quality, accuracy, and reliability. This process is crucial for businesses that rely on data-driven decision-making, as poor data quality can lead to costly mistakes and inefficiencies.

Cost-Benefit 52

Cost-Benefit Data Collection Finance Reporting 52

Ontotext

NOVEMBER 16, 2023

Data mesh solves this by promoting data autonomy, allowing users to make decisions about domains without a centralized gatekeeper. It also improves development velocity with better data governance and access with improved data quality aligned with business needs.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Alation

JANUARY 26, 2023

Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? 2) Always Remember Compliance Source: Unsplash There are now many different data privacy and security laws worldwide.

Data Governance 52

Data Governance Strategy Data Quality Data Collection 52

Alation

MAY 16, 2023

Machine Learning Data pipelines feed all the necessary data into machine learning algorithms, thereby making this branch of Artificial Intelligence (AI) possible. Data Quality When using a data pipeline, data consistency, quality, and reliability are often greatly improved.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

Alation

FEBRUARY 13, 2020

Benefits of a Data Catalog. What Does a Data Catalog Do? A modern data catalog includes many features and functions that all depend on the core capability of cataloging data—collecting the metadata that identifies and describes the inventory of shareable data. Conclusion.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

FineReport

MAY 31, 2023

Finance and accounting teams often deal with data residing in multiple systems, such as accounting software, ERP systems, spreadsheets, and data warehouses. Ensuring seamless data integration and accuracy across these sources can be complex and time-consuming.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

Domino Data Lab

JULY 22, 2019

The data governance, however, is still pretty much over on the data warehouse. Toward the end of the 2000s is when you first started getting teams and industry, as Josh Willis was showing really brilliantly last night, you first started getting some teams identified as “data science” teams. You know what?

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Domino Data Lab

FEBRUARY 4, 2019

These two points provide a different kind of risk management mechanism which is effective for science, specifically data science. Of course, some questions in business cannot be answered with historical data. Instead they require investment, tooling, and time for data collection.

Data Science 66

Data Science Experimentation Machine Learning Data-driven 66

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. CIOs should first understand the different approaches to observing data and how it differs from quality management,” he notes.

Data Strategy 145

Data Strategy Strategy Enterprise Consulting 145

CIO Business Intelligence

OCTOBER 2, 2024

With different people filtering and augmenting data, you need to trace who makes which changes and why, and you need to know which version of the data set was used to train a given model. And with all the data an enterprise has to manage, it’s essential to automate the processes of data collection, filtering, and categorization.

Management 141

Management Data Governance Cost-Benefit Structured Data 141

datapine

AUGUST 29, 2022

Most people are aware that companies collect our GPS locale, text messages, credit card purchases, social media posts, Google search history, etc., and this book will give you an insight into their data collecting procedures and the reasons behind them.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Rocket-Powered Data Science

MARCH 20, 2023

We live in a data-rich, insights-rich, and content-rich world. Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. As you would guess, maintaining context relies on metadata.

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Machine Learning 325

datapine

FEBRUARY 22, 2022

This should also include creating a plan for data storage services. Are the data sources going to remain disparate? Or does building a data warehouse make sense for your organization? Businesses deal with massive amounts of data from their users that can be sensitive and needs to be protected. Define a budget.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Dashboards 218

erwin

JULY 17, 2019

Once you’ve determined what part(s) of your business you’ll be innovating — the next step in a digital transformation strategy is using data to get there. Constructing A Digital Transformation Strategy: Data Enablement. Many organizations prioritize data collection as part of their digital transformation strategy.

Digital Transformation 98

Digital Transformation Strategy Metadata Data-driven 98

DataKitchen

JUNE 24, 2021

Previously we would have a very laborious data warehouse or data mart initiative and it may take a very long time and have a large price tag. Automate the data collection and cleansing process. Jim Tyo added that in the financial services world, agility is critical. Take a show-me approach.

Metrics 211

Metrics ROI Measurement Cost-Benefit 211

Alation

AUGUST 26, 2021

Data intelligence first emerged to support search & discovery, largely in service of analyst productivity. For years, analysts in enterprises had struggled to find the data they needed to build reports. This problem was only exacerbated by explosive growth in data collection and volume. Data lineage features.

Metadata 64

Metadata Data Governance Dashboards Software 64

CIO Business Intelligence

NOVEMBER 11, 2024

Being a manufacturing organization, industrial automation tech is at the heart of our digitization strategy – IOT, AI/ML, RPA, Robotics, intelligent automation, and eventually collating all data in a Data Warehouse to drive analytical insights.

Reporting 96

Reporting IoT Data Collection Data Quality 96

IBM Big Data Hub

AUGUST 4, 2023

Data fabric Data fabric architectures are designed to connect data platforms with the applications where users interact with information for simplified data access in an organization and self-service data consumption. This results in more marketable AI-driven products and greater accountability.

Data Architecture 59

Data Architecture Data Lake Machine Learning Data Governance 59

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

APRIL 14, 2022

Having accurate data is crucial to this process, but finance teams struggle to easily access and connect with data. Improve data quality. Δ The post Automate Your Yardi Real Estate Data Collection and Management appeared first on insightsoftware. Near real-time information is vital to: Save time.

Data Collection 52

Data Collection Management Finance Reporting 52

Jet Global

MARCH 4, 2024

What is the best way to collect the data required for CSRD disclosure? The best way to collect the data required for CSRD disclosure is to use a system that can automate and streamline the data collection process, ensure the data quality and consistency, and facilitate the data analysis and reporting.

Reporting 52

Reporting Management Cost-Benefit Publishing 52

Jet Global

MARCH 4, 2024

Moving data across siloed systems is time-consuming and prone to errors, hurting data quality and reliability. Built on proven technology trusted by thousands, it delivers investor-grade data with robust controls, audit trails, and security. It’s not just a solution, it’s a partnership for a greener future.

Reporting 52

Reporting Data-driven Metrics Software 52

Jet Global

MAY 16, 2022

And using data collected during a close to make smart company decisions outside of finance is an emerging expectation for the Office of the CFO. This means real-time validation on XBRL documents to instantly flag any errors to improve overall quality in first and subsequent filings.

Finance 52

Finance Reporting Management Software 52