IBM Big Data Hub

FEBRUARY 9, 2023

In our last blog , we delved into the seven most prevalent data challenges that can be addressed with effective data governance. Today we will share our approach to developing a data governance program to drive data transformation and fuel a data-driven culture.

Data Governance 83

Data Governance Business Objectives Strategy Data Quality 83

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. So questions linger about whether transformed data can be trusted.

Data Governance 40

Data Governance Risk Metadata Management 40

Sisense

OCTOBER 15, 2020

Every data professional knows that ensuring data quality is vital to producing usable query results. Streaming data can be extra challenging in this regard, as it tends to be “dirty,” with new fields that are added without warning and frequent mistakes in the data collection process. Now, let’s connect to Redshift.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

AWS Big Data

DECEMBER 21, 2023

OpenSearch Service also has vector database capabilities that let you implement semantic search and Retrieval Augmented Generation (RAG) with large language models (LLMs) to build recommendation and media search engines. AWS Glue provides both visual and code-based interfaces to make data integration effortless.

Analytics 96

Analytics IT Data Lake Visualization 96

DataRobot Blog

MARCH 10, 2022

By enabling data scientists to rapidly iterate through model development, validation, and deployment, DataRobot provides the tools to blitz through steps four and five of the machine learning lifecycle with AutoML and Auto Time-Series capabilities. Train, Compare, Rank, Validate, and Select Models for Production.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52

Ontotext

MARCH 27, 2024

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. Knowledge graphs model knowledge of a domain as a graph with a network of entities and relationships.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

Ontotext

NOVEMBER 18, 2021

OntoRefine is a data transformation tool that lets you unite plenty of data formats and get them into your triplestore. Ensuring data quality with SHACL. Our previous step covers data format differences. Dealing with spreadsheets via OntoRefine. Surveyors already use spreadsheets. Everyone makes mistakes.

Visualization 98

Visualization Reporting Metadata Enterprise 98

AWS Big Data

APRIL 19, 2023

Background The success of a data-driven organization recognizes data as a key enabler to increase and sustain innovation. The goal of a data product is to solve the long-standing issue of data silos and data quality. It follows what is called a distributed system architecture.

Technology 82

Technology Data-driven Machine Learning Sales 82

IBM Big Data Hub

JANUARY 9, 2024

Companies still often accept the risk of using internal data when exploring large language models (LLMs) because this contextual data is what enables LLMs to change from general-purpose to domain-specific knowledge. In the generative AI or traditional AI development cycle, data ingestion serves as the entry point.

Enterprise 80

Enterprise Data Integration Data Quality Contextual Data 80

CIO Business Intelligence

JUNE 23, 2022

Yet as companies fight for skilled analyst roles to utilize data to make better decisions , they often fall short in improving the data supply chain and resulting data quality. Without a solid data supply-chain management practices in place, data quality often suffers. First mile/last mile impacts.

Data Quality 98

Data Quality Key Performance Indicator Metrics KPI 98

CIO Business Intelligence

DECEMBER 6, 2023

However, this partnership model cannot keep pace with an always-changing technology landscape in which the skill gaps and lack of resources are increasing. The new models recognise this, drawing tech vendors to shift toward innovation-focused roles and become partners in the client’s success.

Digital Transformation 116

Digital Transformation Software Cost-Benefit Modeling 116

Peter James Thomas

OCTOBER 30, 2018

It may well be that one thing that a CDO needs to get going is a data transformation programme. This may purely be focused on cultural aspects of how an organisation records, shares and otherwise uses data. It may be to build a new (or a first) Data Architecture. It may be to build a new (or a first) Data Architecture.

Marketing 51

Marketing Strategy Data Architecture Data Strategy 51

CIO Business Intelligence

DECEMBER 22, 2022

It seeks to improve the way data are managed and products are created, and to coordinate these improvements with the goals of the business. According to Gartner, DataOps also aims “to deliver value faster by creating predictable delivery and change management of data, data models, and related artifacts.”

Analytics 130

Analytics Machine Learning Software Data Quality 130

Alation

OCTOBER 18, 2022

Yet every dbt transformation contains vital metadata that is not captured – until now. Making this data visible in the data catalog will let data teams share their work, support re-use, and empower everyone to better understand and trust data. Data Transformation in the Modern Data Stack.

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

erwin

MARCH 4, 2021

So companies will be forced to classify their data and to find mechanisms to share it with such platforms.”. GDPR is also proving to be the de facto model for data privacy across the United States. You can request a demo of erwin Data Intelligence here.

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

AWS Big Data

JULY 20, 2023

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. Moreover, running advanced analytics and ML on disparate data sources proved challenging.

Data Lake 87

Data Lake Analytics Snapshot Optimization 87

Alation

OCTOBER 28, 2021

Healthcare is changing, and it all comes down to data. Leaders in healthcare seek to improve patient outcomes, meet changing business models (including value-based care ), and ensure compliance while creating better experiences. Data & analytics represents a major opportunity to tackle these challenges.

Data Governance 52

Data Governance Measurement Modeling Metrics 52

IBM Big Data Hub

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

Cost-Benefit 84

Cost-Benefit Metadata Optimization Management 84

AWS Big Data

MARCH 3, 2023

Finally, data integrity is of paramount importance. Every event in the data source can be relevant, and our customers don’t tolerate data loss, poor data quality, or discrepancies between the source and Tricentis Analytics. Fixed-size data files avoid further latency due to unbound file sizes.

Software 52

Software Data Lake Testing Cost-Benefit 52

erwin

APRIL 16, 2024

In this blog, we’ll delve into the critical role of governance and data modeling tools in supporting a seamless data mesh implementation and explore how erwin tools can be used in that role. erwin also provides data governance, metadata management and data lineage software called erwin Data Intelligence by Quest.

Metadata 52

Metadata Data Quality Data Governance Modeling 52

DataKitchen

APRIL 26, 2021

Furthermore, the introduction of AI and ML models hastened the need to be more efficient and effective in deploying new technologies. Similarly, Workiva was driven to DataOps due to an increased need for analytics agility to meet a range of organizational needs, such as real-time dashboard updates or ML model training and monitoring.

Measurement 246

Measurement Metrics Data-driven Testing 246

CIO Business Intelligence

NOVEMBER 7, 2023

Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever. The aim is to normalize, aggregate, and eventually make available to analysts across the organization data that originates in various pockets of the enterprise.

Data Warehouse 142

Data Warehouse Digital Transformation Data-driven Reporting 142

Smart Data Collective

OCTOBER 13, 2021

There are countless examples of big data transforming many different industries. There is no disputing the fact that the collection and analysis of massive amounts of unstructured data has been a huge breakthrough. How does Data Virtualization manage data quality requirements?

Visualization 133

Visualization Cost-Benefit Big Data Prescriptive Analytics 133

Rocket-Powered Data Science

MARCH 20, 2023

Datasphere goes beyond the “big three” data usage end-user requirements (ease of discovery, access, and delivery) to include data orchestration (data ops and data transformations) and business data contextualization (semantics, metadata, catalog services).

Data Warehouse 324

Data Warehouse Metadata Digital Transformation Unstructured Data 324

Ontotext

FEBRUARY 12, 2024

This is especially beneficial when teams need to increase data product velocity with trust and data quality, reduce communication costs, and help data solutions align with business objectives. In most enterprises, data is needed and produced by many business units but owned and trusted by no one.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

DataKitchen

JANUARY 23, 2023

It allows organizations to see how data is being used, where it is coming from, its quality, and how it is being transformed. DataOps Observability includes monitoring and testing the data pipeline, data quality, data testing, and alerting. Data lineage does not directly improve data quality.

Testing 130

Testing Data Governance Data Quality Data-driven 130

Alation

NOVEMBER 22, 2022

What Is Data Governance In The Public Sector? Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

Jet Global

MAY 28, 2019

A data warehouse stores transactional level details and serves the broader reporting and analytical needs of an organization – creating one source of truth for building semantic models or serving structured, simplified and harmonized data to tools like Power BI, Excel or even SSRS.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

AWS Big Data

APRIL 5, 2023

“Each of these tools were getting data from a different place, and that’s where it gets difficult,” says Jeroen Minnaert, head of data at Showpad. “If If each tool tells a different story because it has different data, we won’t have alignment within the business on what this data means.” With QuickSight, we pay for usage.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

Jet Global

AUGUST 24, 2023

Although many companies run their own on-premises servers to maintain IT infrastructure, nearly half of organizations already store data on the public cloud. The Harvard Business Review study finds that 88% of organizations that already have a hybrid model in place see themselves maintaining the same strategy into the future.

Finance 52

Finance Reporting Data Integration Risk 52

Jet Global

FEBRUARY 23, 2024

Data mapping is essential for integration, migration, and transformation of different data sets; it allows you to improve your data quality by preventing duplications and redundancies in your data fields. Data mapping is important for several reasons.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

MARCH 14, 2024

Mastering Data: Effectively Manage Your Data Download Now How Jet Analytics Enhances Microsoft Fabric Jet Analytics from insightsoftware is a complete data preparation, automation and modeling solution that enables Microsoft Dynamics customers to accelerate Dynamics ERP-ready BI projects without requiring specialist skills.

Analytics 52

Analytics Management Reporting Enterprise 52

Jet Global

MARCH 13, 2024

Complex Data Structures and Integration Processes Dynamics data structures are already complex – finance teams navigating Dynamics data frequently require IT department support to complete their routine reporting.

Reporting 52

Reporting Finance Data Quality Sales 52