CIO Business Intelligence

FEBRUARY 27, 2025

Additionally, integrating mainframe data with the cloud enables enterprises to feed information into data lakes and data lake houses, which is ideal for authorized data professionals to easily leverage the best and most modern tools for analytics and forecasting. Four key challenges prevent them from doing so: 1.

Metadata 88

Metadata Data Lake Cost-Benefit Forecasting 88

AWS Big Data

JULY 26, 2023

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. Are there recommended approaches to provisioning components for data integration?

Data Integration 97

Data Integration Snapshot Testing Visualization 97

AWS Big Data

JANUARY 15, 2025

While real-time data is processed by other applications, this setup maintains high-performance analytics without the expense of continuous processing. This agility accelerates EUROGATEs insight generation, keeping decision-making aligned with current data.

IoT 111

IoT Machine Learning Metadata Data-driven 111

AWS Big Data

DECEMBER 16, 2024

Third, some services require you to set up and manage compute resources used for federated connectivity, and capabilities like connection testing and data preview arent available in all services. To solve for these challenges, we launched Amazon SageMaker Lakehouse unified data connectivity.

Visualization 93

Visualization Data Processing Testing Publishing 93

Ontotext

AUGUST 24, 2023

The second approach is to use some Data Integration Platform. As an enterprise-supported tool, it has already established how to make all data transformations. Then the recommended approach is to use one of the many JSON to RDF transformation frameworks to produce RDF data.

Data Integration 52

Data Integration Modeling Business Objectives Optimization 52

DataKitchen

NOVEMBER 10, 2023

Implement a communication protocol that swiftly informs stakeholders, allowing them to brace for or address the potential impacts of the data change. Building a Culture of Accountability: Encourage a culture where data integrity is everyone’s responsibility.

Data Quality 139

Data Quality Testing Data Lake Data Integration 139

DataKitchen

DECEMBER 20, 2020

The DataOps Engineering skillset includes hybrid and cloud platforms, orchestration, data architecture, data integration, data transformation, CI/CD, real-time messaging, and containers. The role of the DataOps Engineer goes by several different titles and is sometimes covered by IT, dev, or analyst functions.

Data-driven 147

Data-driven Manufacturing Data Architecture Data Analytics 147

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. Azure Blob Storage serves as the data lake to store raw data.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 111

Metadata Data Lake Visualization Data Quality 111

IBM Big Data Hub

JANUARY 9, 2024

This may also entail working with new data through methods like web scraping or uploading. Data governance is an ongoing process in the data lifecycle to help ensure compliance with laws and company best practices. Data integration: These tools enable companies to combine disparate data sources into one secure location.

Enterprise 71

Enterprise Data Integration Data Quality Contextual Data 71

AWS Big Data

OCTOBER 27, 2023

Data integration is the foundation of robust data analytics. It encompasses the discovery, preparation, and composition of data from diverse sources. In the modern data landscape, accessing, integrating, and transforming data from diverse sources is a vital process for data-driven decision-making.

Analytics 124

Analytics Visualization Data Integration Cost-Benefit 124

AWS Big Data

JANUARY 30, 2025

AWS Glue A data integration service, AWS Glue consolidates major data integration capabilities into a single service. These include data discovery, modern ETL, cleansing, transforming, and centralized cataloging. Its also serverless, which means theres no infrastructure to manage.

Data Warehouse 54

Data Warehouse Data Architecture Machine Learning Data Transformation 54

AWS Big Data

AUGUST 19, 2024

As organizations increasingly rely on data stored across various platforms, such as Snowflake , Amazon Simple Storage Service (Amazon S3), and various software as a service (SaaS) applications, the challenge of bringing these disparate data sources together has never been more pressing.

Analytics 119

Analytics Data-driven Data Integration Data Lake 119

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. Does Data Virtualization support web data integration?

Visualization 145

Visualization Cost-Benefit Big Data Prescriptive Analytics 145

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.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

AWS Big Data

DECEMBER 21, 2023

Movement of data across data lakes, data warehouses, and purpose-built stores is achieved by extract, transform, and load (ETL) processes using data integration services such as AWS Glue. AWS Glue provides both visual and code-based interfaces to make data integration effortless.

Analytics 111

Analytics IT Data Lake Visualization 111

AWS Big Data

JANUARY 6, 2025

With Amazon AppFlow, you can run data flows at nearly any scale and at the frequency you chooseon a schedule, in response to a business event, or on demand. You can configure data transformation capabilities such as filtering and validation to generate rich, ready-to-use data as part of the flow itself, without additional steps.

Analytics 98

Analytics Data Warehouse Metrics Big Data 98

AWS Big Data

NOVEMBER 13, 2023

As Gameskraft’s portfolio of gaming products increased, it led to an approximate five-times growth of dedicated data analytics and data science teams. Consequently, there was a fivefold rise in data integrations and a fivefold increase in ad hoc queries submitted to the Redshift cluster.

Data Warehouse 111

Data Warehouse Analytics Data Lake Data Science 111

Dataiku

JUNE 26, 2019

Last year when we surveyed over one hundred data professionals, they ranked organizational change as their third biggest data challenge (behind data cleaning and model productionalization).

Data Integration 95

Data Integration Modeling Data Transformation 95

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. We will create a glue studio job, add events and venue data from the SFTP server, carry out data transformations and load transformed data to s3.

Data Processing 115

Data Processing Visualization Data Lake Data Processing 115

CIO Business Intelligence

JANUARY 9, 2023

To fuel self-service analytics and provide the real-time information customers and internal stakeholders need to meet customers’ shipping requirements, the Richmond, VA-based company, which operates a fleet of more than 8,500 tractors and 34,000 trailers, has embarked on a data transformation journey to improve data integration and data management.

Data Strategy 111

Data Strategy Strategy Data Governance Marketing 111

erwin

APRIL 29, 2020

Many large organizations, in their desire to modernize with technology, have acquired several different systems with various data entry points and transformation rules for data as it moves into and across the organization. Business terms and data policies should be implemented through standardized and documented business rules.

Key Performance Indicator 111

Key Performance Indicator Metadata Data Governance Data Quality 111

CIO Business Intelligence

JUNE 7, 2022

Data analytics draws from a range of disciplines — including computer programming, mathematics, and statistics — to perform analysis on data in an effort to describe, predict, and improve performance. What are the four types of data analytics?

Data Analytics 135

Data Analytics Diagnostic Analytics Management Analytics 135

CIO Business Intelligence

JANUARY 24, 2024

“Rather, structure data teams to be organizationally centralized [and] physically co-located with the business — with objectives aligned to that business.” This approach helps to establish a unified data ecosystem that enables seamless data integration, sharing, and collaboration across the organization, Swann says.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

DataKitchen

DECEMBER 9, 2022

DataOps automation typically involves the use of tools and technologies to automate the various steps of the data analytics and machine learning process, from data preparation and cleaning, to model training and deployment. The data scientists and IT professionals were amazed, and they couldn’t believe their eyes.

Machine Learning 130

Machine Learning Data-driven Optimization Data Analytics 130

DataKitchen

OCTOBER 25, 2022

It’s because it’s a hard thing to accomplish when there are so many teams, locales, data sources, pipelines, dependencies, data transformations, models, visualizations, tests, internal customers, and external customers. You can’t quality-control your data integrations or reports with only some details. .

Testing 130

Testing Data-driven Visualization Dashboards 130

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. Zenia Graph’s Salesforce Accelerator makes this a reality.

Data-driven 52

Data-driven Strategy Sales Data Integration 52

Cloudera

JUNE 1, 2021

These acquisitions usher in a new era of “ self-service ” by automating complex operations so customers can focus on building great data-driven apps instead of managing infrastructure. Datacoral powers fast and easy data transformations for any type of data via a robust multi-tenant SaaS architecture that runs in AWS.

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

AWS Big Data

OCTOBER 11, 2023

Due to this low complexity, the solution uses AWS serverless services to ingest the data, transform it, and make it available for analytics. The data ingestion process copies the machine-readable files from the hospitals, validates the data, and keeps the validated files available for analysis.

Visualization 119

Visualization Dashboards Data-driven Gap analysis 119

AWS Big Data

SEPTEMBER 13, 2024

To share data to our internal consumers, we use AWS Lake Formation with LF-Tags to streamline the process of managing access rights across the organization. Data integration workflow A typical data integration process consists of ingestion, analysis, and production phases.

Interactive 109

Interactive Strategy Cost-Benefit Data Governance 109

IBM Big Data Hub

JULY 28, 2023

As an independent software vendor (ISV), we at Primeur embed the Open Liberty Java runtime in our flagship data integration platform, DATA ONE. Primeur and DATA ONE As a smart data integration company, we at Primeur believe in simplification. Data Shaper , providing any-to-any data transformations.

Data Integration 55

Data Integration Optimization Software Insurance 55

Sisense

AUGUST 6, 2020

As an AI product manager, here are some important data-related questions you should ask yourself: What is the problem you’re trying to solve? What data transformations are needed from your data scientists to prepare the data? What are the right KPIs and outputs for your product? What will it take to build your MVP?

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

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

AWS Big Data

JULY 25, 2023

About Talend Talend is an AWS ISV Partner with the Amazon Redshift Ready Product designation and AWS Competencies in both Data and Analytics and Migration. Talend Cloud combines data integration, data integrity, and data governance in a single, unified platform that makes it easy to collect, transform, clean, govern, and share your data.

Data Analytics 52

Data Analytics Analytics Data Warehouse Data Processing 52

Alation

JANUARY 17, 2023

What if, experts asked, you could load raw data into a warehouse, and then empower people to transform it for their own unique needs? Today, data integration platforms like Rivery do just that. By pushing the T to the last step in the process, such products have revolutionized how data is understood and analyzed.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Science Data Transformation 52

Octopai

JUNE 9, 2024

By embracing automated, multidimensional data lineage, HealthCo was able to maintain a consistent and reliable data environment across their hybrid systems. Solving the data lineage problem directly supported their data products by ensuring data integrity and reliability.

IT 52

IT Data-driven Predictive Analytics Data Strategy 52

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.

Data Governance 40

Data Governance Risk Metadata Management 40