CIO Business Intelligence

FEBRUARY 16, 2023

But to augment its various businesses with ML and AI, Iyengar’s team first had to break down data silos within the organization and transform the company’s data operations. Digitizing was our first stake at the table in our data journey,” he says. The offensive side?

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

Smart Data Collective

APRIL 29, 2020

A survey from Tech Pro Research showed that 70 percent of organisations already have a digital transformation strategy or are developing one. Solutions for the various data management processes need to be carefully considered. The techniques for managing organisational data in a standardised approach that minimises inefficiency.

Management 85

Management Data Warehouse Digital Transformation Dashboards 85

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. Conclusion Data-driven organizations are transitioning to a data product way of thinking.

Technology 80

Technology Data-driven Machine Learning Sales 80

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

erwin

SEPTEMBER 17, 2020

Here are six benefits of automating end-to-end data lineage: Reduced Errors and Operational Costs. Data quality is crucial to every organization. Automated data capture can significantly reduce errors when compared to manual entry. However, different types of data need to be treated differently.

Cost-Benefit 143

Cost-Benefit Data Governance Metadata Reporting 143

Peter James Thomas

OCTOBER 30, 2018

Prelude… I recently came across an article in Marketing Week with the clickbait-worthy headline of Why the rise of the chief data officer will be short-lived (their choice of capitalisation). It may well be that one thing that a CDO needs to get going is a data transformation programme. It may be to improve Data Quality.

Marketing 51

Marketing Strategy Data Architecture Data Strategy 51

DataRobot Blog

MARCH 10, 2022

This is currently a widespread strategy across the industry where we are seeing companies move from reactive to predictive inventory management and capacity planning. The first step in building a model that can predict machine failure and even recommend the next best course of action is to aggregate, clean, and prepare data to train against.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52

CIO Business Intelligence

DECEMBER 6, 2023

Often, tech vendors act as an extended workforce, providing manpower and technological expertise for their client’s digital transformation journey. When taking this to the next level, vendor partners act as co-innovators, helping businesses craft winning strategies based on innovation.

Digital Transformation 116

Digital Transformation Software Cost-Benefit Modeling 116

CIO Business Intelligence

DECEMBER 22, 2022

“This style of organization is useful for any data-oriented work, making it easier to take advantage of the benefits offered by building a global data fabric.” Analytics, Collaboration Software, Data Management, Data Mining, Data Science, IT Strategy, Small and Medium Business.

Analytics 130

Analytics Machine Learning Software Data Quality 130

AWS Big Data

FEBRUARY 8, 2023

It’s common to ingest multiple data sources into Amazon Redshift to perform analytics. Often, each data source will have its own processes of creating and maintaining data, which can lead to data quality challenges within and across sources. Answering questions as simple as “How many unique customers do we have?”

Data Quality 75

Data Quality Testing Data Warehouse Unstructured Data 75

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

Alation

AUGUST 11, 2022

But there are only so many data engineers available in the market today; there’s a big skills shortage. So to get away from that lack of data engineers, what data mesh says is, ‘Take those business logic data transformation capabilities and move that to the domains.’ Let’s take data privacy as an example.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 52

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 86

Data Lake Analytics Snapshot Optimization 86

Octopai

JANUARY 19, 2021

Octopai is the first BI Intelligence platform to analyze Azure Data Factory in hybrid BI environments, providing automated data lineage and discovery and will continue to announce the early support of more platforms as part of an overall strategy to have one centralized view of the entire BI landscape. “We

Metadata 52

Metadata ROI Optimization Data Quality 52

Alation

OCTOBER 28, 2021

To make good on this potential, healthcare organizations need to understand their data and how they can use it. These systems should collectively maintain data quality, integrity, and security, so the organization can use data effectively and efficiently. Why Is Data Governance in Healthcare Important?

Data Governance 52

Data Governance Measurement Modeling Metrics 52

AWS Big Data

MARCH 3, 2023

Additionally, the scale is significant because the multi-tenant data sources provide a continuous stream of testing activity, and our users require quick data refreshes as well as historical context for up to a decade due to compliance and regulatory demands. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

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? In forecasting future events.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

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 Reporting Data-driven 142

DataKitchen

APRIL 26, 2021

In early April 2021, DataKItchen sat down with Jonathan Hodges, VP Data Management & Analytics, at Workiva ; Chuck Smith, VP of R&D Data Strategy at GlaxoSmithKline (GSK) ; and Chris Bergh, CEO and Head Chef at DataKitchen, to find out about their enterprise DataOps transformation journey, including key successes and lessons learned.

Measurement 246

Measurement Metrics Data-driven Testing 246

Ontotext

FEBRUARY 12, 2024

Usually, organizations will combine different domain topologies, depending on the trade-offs, and choose to focus on specific aspects of data mesh. Once accomplished, an effective implementation spurs a mindset in which organizations prioritize and value data for decision-making, formulating strategies, and day-to-day operations.

Data-driven 59

Data-driven Data Lake Data Quality Business Objectives 59

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 is typically used by companies with a high level of data diversity or analytical requirements. As the complexity and volume of data used in the enterprise scales and organizations want to get more out of their analytics efforts, data warehouses are gaining more traction for reporting and analytics over databases.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

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. 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.”

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

Jet Global

AUGUST 24, 2023

According to a recent survey by the Harvard Business Review , 81% of respondents said cloud is very or extremely important to their company’s growth strategy. Although many companies run their own on-premises servers to maintain IT infrastructure, nearly half of organizations already store data on the public cloud.

Finance 52

Finance Reporting Data Integration Risk 52

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Jet Global

MARCH 14, 2024

Jet’s interface lets you handle data administration easily, without advanced coding skills. You don’t need technical skills to manage complex data workflows in the Fabric environment. Data Lineage and Documentation Jet Analytics simplifies the process of documenting data assets and tracking data lineage in Fabric.

Analytics 52

Analytics Management Reporting Enterprise 52