Ontotext

MARCH 20, 2024

In today’s data-driven world, businesses are drowning in a sea of information. Traditional data integration methods struggle to bridge these gaps, hampered by high costs, data quality concerns, and inconsistencies. It’s a huge productivity loss.”

Data-driven 52

Data-driven Strategy Sales Data Integration 52

Analytics Vidhya

APRIL 29, 2022

This article was published as a part of the Data Science Blogathon. Introduction Azure data factory (ADF) is a cloud-based ETL (Extract, Transform, Load) tool and data integration service which allows you to create a data-driven workflow. In this article, I’ll show […].

Data-driven 328

Data-driven Data Transformation Data Science Data Integration 328

Analytics Vidhya

AUGUST 22, 2023

Introduction In today’s data-driven world, seamless data integration plays a crucial role in driving business decisions and innovation. Two prominent methodologies have emerged to facilitate this process: Extract, Transform, Load (ETL) and Extract, Load, Transform (ELT).

Data-driven 267

Data-driven Data Integration Analytics 267

AWS Big Data

AUGUST 19, 2024

In today’s data-driven world, the ability to seamlessly integrate and utilize diverse data sources is critical for gaining actionable insights and driving innovation. The company stores vast amounts of transactional data, customer information, and product catalogs in Snowflake.

Analytics 98

Analytics Data-driven Data Integration Data Lake 98

Sisense

AUGUST 28, 2020

We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways data teams are tackling the challenges of this new world to help their companies and their customers thrive. What is data integrity?

Data Integration 101

Data Integration Testing Data Quality Data-driven 101

Sisense

MARCH 9, 2020

One of the main goals of a digital transformation is to empower everyone within an organization to make smarter, data-driven decisions. Before we dig into what your enterprise data integration will do for your organization, let’s touch briefly on the challenges that collecting all of an enterprise’s data can entail.

Data Integration 93

Data Integration Enterprise Slice and Dice Digital Transformation 93

Data Virtualization

OCTOBER 27, 2023

Kafka is used when real-time data streaming and event-driven architectures with scalable data processing are essential.

Data Integration 52

Data Integration Data-driven Data Processing Management 52

erwin

JANUARY 17, 2020

What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

Data Virtualization

DECEMBER 1, 2022

The post The Prudent Pursuit of ESG Initiatives for Data-Driven Organizations appeared first on Data Virtualization blog - Data Integration and Modern Data Management Articles, Analysis and Information. ESG represents the standards used by socially conscious investors to screen potential investments.

Data-driven 52

Data-driven Data Integration Management IT 52

CIO Business Intelligence

OCTOBER 26, 2023

Business intelligence (BI) analysts transform data into insights that drive business value. The role is becoming increasingly important as organizations move to capitalize on the volumes of data they collect through business intelligence strategies.

Business Intelligence 125

Business Intelligence Data-driven Statistics Data Warehouse 125

AWS Big Data

JULY 26, 2023

Data is a key enabler for your business. Many AWS customers have integrated their data across multiple data sources using AWS Glue , a serverless data integration service, in order to make data-driven business decisions.

Data Integration 73

Data Integration Snapshot Testing Visualization 73

Smarten

SEPTEMBER 29, 2023

The company has grown exponentially, first across France and then throughout the world, driven by the transformation of the business. Smarten provided a comprehensive set of reporting and analytics tools, e.g., Headquarter Sales reports, Stock Transfer Planning, Site Net Sales, Outstanding Summary, Party Sales and many more.

Analytics 69

Analytics Sales Operational Reporting Reporting 69

DataKitchen

DECEMBER 9, 2022

ChatGPT> DataOps, or data operations, is a set of practices and technologies that organizations use to improve the speed, quality, and reliability of their data analytics processes. The goal of DataOps is to help organizations make better use of their data to drive business decisions and improve outcomes.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

AWS Big Data

JUNE 28, 2023

Data is at the center of every application, process, and business decision. When data is used to improve customer experiences and drive innovation, it can lead to business growth. According to Forrester , advanced insights-driven businesses are 8.5 Firstly, it invariably requires data engineers to create custom code.

Analytics 70

Analytics Data Warehouse Data Lake Data-driven 70

AWS Big Data

JUNE 25, 2024

This post is co-authored by Vijay Gopalakrishnan, Director of Product, Salesforce Data Cloud. In today’s data-driven business landscape, organizations collect a wealth of data across various touch points and unify it in a central data warehouse or a data lake to deliver business insights.

Data Lake 103

Data Lake Cost-Benefit Data-driven Data Warehouse 103

FineReport

JUNE 11, 2021

As companies striving to embrace digital transformation and become data-driven, business intelligence and analytics skills and experience are essential to building a data-savvy team. However, if someone puts you on the spot, can you clearly tell the difference between business intelligence and analytics?

Business Intelligence 98

Business Intelligence Analytics Dashboards Statistics 98

DataKitchen

JANUARY 25, 2022

Analytics are prone to frequent data errors and deployment of analytics is slow and laborious. The strategic value of analytics is widely recognized, but the turnaround time of analytics teams typically can’t support the decision-making needs of executives coping with fast-paced market conditions.

Consulting 244

Consulting Testing Data Lake Data Quality 244

CIO Business Intelligence

APRIL 28, 2022

Right from the start, auxmoney leveraged cloud-enabled analytics for its unique risk models and digital processes to further its mission. Particularly in Asia Pacific , revenues for big data and analytics solutions providers hit US$22.6bn in 2020 , with financial services companies ranking among their biggest clients.

Analytics 98

Analytics Insurance Big Data Uncertainty 98

AWS Big Data

SEPTEMBER 3, 2024

Data is a key driver for your business. Data volume can increase significantly over time, and it often requires concurrent consumption of large compute resources. Data integration workloads can become increasingly concurrent as more and more applications demand access to data at the same time.

Data Integration 95

Data Integration Software Data-driven Big Data 95

BizAcuity

MAY 24, 2022

IaaS provides a platform for compute, data storage and networking capabilities. IaaS is mainly used for developing softwares (testing and development, batch processing), hosting web applications and data analysis. Analytics as a Service (AaaS). To try and test the platforms in accordance with data strategy and governance.

Data-driven 52

Data-driven Cost-Benefit Digital Transformation Strategy 52

BizAcuity

MAY 4, 2021

In today’s data-powered world with data fueling everything from essential management systems to customer-focused AI solutions , one thing that often gets in the way is data fragmentation. . Why Data integration plays a vital role for gaming companies? Naturally, the player journey is segmented into six parts, .

Data Integration 40

Data Integration Cost-Benefit Optimization Behavioral Analytics 40

AWS Big Data

NOVEMBER 28, 2023

As customers become more data driven and use data as a source of competitive advantage, they want to easily run analytics on their data to better understand their core business drivers to grow sales, reduce costs, and optimize their businesses. But integrating data isn’t easy.

Data Warehouse 97

Data Warehouse Data-driven Machine Learning B2B 97

CIO Business Intelligence

JULY 18, 2024

Emerging technologies are transforming organizations of all sizes, but with the seemingly endless possibilities they bring, they also come with new challenges surrounding data management that IT departments must solve. This is why data discovery and data transparency are so important.

Management 109

Management Internet of Things IoT Metadata 109

Smarten

SEPTEMBER 28, 2022

Apply Predictive Analytics to Specific Business Use Cases for Real Results! Gartner has predicted that, ‘Overall analytics adoption will increase from 35% to 50%, driven by vertical and domain-specific augmented analytics solutions.’ Predictive Analytics Using External Data. Plan and forecast accurately.’.

Predictive Analytics 52

Predictive Analytics Analytics Predictive Modeling Forecasting 52

DataKitchen

OCTOBER 20, 2023

In today’s data-driven landscape, Data and Analytics Teams i ncreasingly face a unique set of challenges presented by Demanding Data Consumers who require a personalized level of Data Observability. Data Observability platforms often need to deliver this level of customization.

Insurance 169

Insurance Metadata Data-driven Data Quality 169

CIO Business Intelligence

AUGUST 22, 2024

Salesforce is a vendor of cloud-based software and applications for sales, customer service, marketing automation, ecommerce, analytics, and application development. July 26, 2024: Salesforce and Workday are partnering to build a new AI-based employee service agent based on a common data foundation. Based in San Francisco, Calif.,

Sales 90

Sales Data-driven Software Marketing 90

Data Virtualization

JANUARY 18, 2024

Reading Time: 3 minutes Today, the most innovative and successful organizations leverage data to increase revenue, minimize expenses, and deliver products and services that meet the needs of their customers. To be truly “data-driven,” an organization must view data as more than a byproduct. The post How to Shop for Data?

Data-driven 59

Data-driven Data Integration Management Metadata 59

Andrew White

OCTOBER 5, 2020

Afraz Jaffri scored his second “number 1” hit last with with a re-entry: How to Build Knowledge Graphs That Enable AI-Driven Enterprise Applications. This note was our most-read note across all of Data and Analytics excluding any branded research such as Magic Quadrants etc.

Analytics 52

Analytics Data-driven Interactive Data Integration 52

AWS Big Data

NOVEMBER 15, 2023

For organizations seeking to unlock innovation with data and AI, AWS re:Invent 2023 offers several opportunities. Attendees will discover services, strategies, and solutions for tackling any data challenge. Keynotes Several keynotes will shine a spotlight on data. Keynotes Several keynotes will shine a spotlight on data.

Broadcasting 117

Broadcasting Recreation/Entertainment Data Governance Strategy 117

DataKitchen

DECEMBER 20, 2020

Data-driven companies sense change through data analytics. Analytics tell the story of markets and customers. Analytics enable companies to understand their environment. Companies turn to their data organization to provide the analytics that stimulates creative problem-solving.

Data-driven 147

Data-driven Manufacturing Data Architecture Data Analytics 147

CIO Business Intelligence

MAY 9, 2024

In today’s data-driven world, the ability to seamlessly integrate structured and unstructured data in a hybrid cloud environment is critical for organizations seeking to harness the full potential of their data assets.

Digital Transformation 52

Digital Transformation Data Integration Unstructured Data Data-driven 52

FineReport

JUNE 11, 2021

As companies striving to embrace digital transformation and become data-driven, business intelligence and analytics skills and experience are essential to building a data-savvy team. However, if someone puts you on the spot, can you clearly tell the difference between business intelligence and analytics?

Business Intelligence 52

Business Intelligence Analytics Dashboards Statistics 52

Smart Data Collective

APRIL 15, 2021

Business Intelligence is the practice of collecting and analyzing data and transforming it into useful, actionable information. Business Intelligence uses methods and tools like machine learning to take massive, unstructured swaths of data and turn them into easy-to-use reports. Set Up Data Integration.

Business Intelligence 96

Business Intelligence Analytics Statistics Data Warehouse 96

IBM Big Data Hub

JUNE 29, 2023

Integrated planning incorporates supply chain planning, demand planning, and demand forecasts so the company can quickly assess the impact on inventory levels, supply chain logistics, production plans, and customer service capacity. Data integration and analytics IBP relies on the integration of data from different sources and systems.

Key Performance Indicator 76

Key Performance Indicator Forecasting Sales Data Integration 76

DataKitchen

MAY 10, 2024

The Five Use Cases in Data Observability: Mastering Data Production (#3) Introduction Managing the production phase of data analytics is a daunting challenge. Overseeing multi-tool, multi-dataset, and multi-hop data processes ensures high-quality outputs.

Metrics 124

Metrics Testing Data Quality Dashboards 124

AWS Big Data

AUGUST 13, 2024

In today’s data-driven world, seamless integration and transformation of data across diverse sources into actionable insights is paramount. With AWS Glue, you can discover and connect to hundreds of diverse data sources and manage your data in a centralized data catalog.

Data Processing 90

Data Processing Visualization Data Lake Data Processing 90

Rocket-Powered Data Science

JULY 6, 2021

Specifically, in the modern era of massive data collections and exploding content repositories, we can no longer simply rely on keyword searches to be sufficient. My favorite approach to TAM creation and to modern data management in general is AI and machine learning (ML). Data catalogs are very useful and important.

Strategy 267

Strategy Machine Learning Metadata Knowledge Discovery 267