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 136

Data Quality Testing Data Lake Data Integration 136

CIO Business Intelligence

MARCH 4, 2024

In this way, data may just be the ultimate disruptor – a fact that the insurance industry knows all too well. As data volumes continue to increase alongside a correlating number of business requests, modern insurance data leaders face a nuanced set of challenges. Enter data mesh.

Insurance 78

Insurance Strategy Data Governance Data Integration 78

DataKitchen

JULY 27, 2023

We counted ten ‘standard’ ways to transform and set up batch data pipelines in Microsoft Azure. 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.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

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. What Does Data Mapping Involve?

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

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 91

Metadata Data Lake Visualization Data Transformation 91

AWS Big Data

MAY 9, 2023

Hundreds of thousands of customers use AWS Glue , a serverless data integration service, to discover, prepare, and combine data for analytics, machine learning (ML), and application development. AWS Glue for Apache Spark jobs work with your code and configuration of the number of data processing units (DPU). Generally, G.2X

Data Lake 91

Data Lake Cost-Benefit Data Integration Data Transformation 91

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

Jet Global

MAY 6, 2024

This untapped potential suggests a significant opportunity for those willing to embrace AI and gain a competitive edge through intelligent automation and data-driven financial insights. Seek reporting solutions designed to conquer these data wrangling challenges and ensure a smooth workflow for optimizing Oracle Cloud ERP’s AI features.

Finance 52

Finance Reporting Data Transformation Optimization 52

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 98

Analytics Visualization Data Integration Cost-Benefit 98

DataKitchen

DECEMBER 20, 2020

Data-driven companies sense change through data analytics. Companies turn to their data organization to provide the analytics that stimulates creative problem-solving. Companies turn to their data organization to provide the analytics that stimulates creative problem-solving. – Leon C. Adapt or face decline.

Data-driven 147

Data-driven Manufacturing Data Architecture Data Analytics 147

Jet Global

MAY 9, 2024

Change Data : A method of tracking and capturing changes made to data in a database or data source, including monitoring inserts, updates, and deletes to data records in real-time or near-real-time for the purpose of keeping downstream systems, such as data warehouses, data lakes, or other applications, in sync with the source data systems.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

CIO Business Intelligence

NOVEMBER 7, 2023

For years, IT and business leaders have been talking about breaking down the data silos that exist within their organizations. Given the importance of sharing information among diverse disciplines in the era of digital transformation, this concept is arguably as important as ever.

Data Warehouse 136

Data Warehouse Digital Transformation Data-driven Reporting 136

CIO Business Intelligence

FEBRUARY 16, 2023

The company’s orthodontics business, for instance, makes heavy use of image processing to the point that unstructured data is growing at a pace of roughly 20% to 25% per month. For example, imaging data can be used to show patients how an aligner will change their appearance over time. “It

Unstructured Data 98

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 98

FineReport

MARCH 31, 2024

Furthermore, these tools boast customization options, allowing users to tailor data sources to address areas critical to their business success, thereby generating actionable insights and customizable reports. Best BI Tools for Data Analysts 3.1

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These query patterns and concurrency were unpredictable in nature.

Data Warehouse 94

Data Warehouse Data Lake Analytics Data Science 94

CIO Business Intelligence

JANUARY 24, 2024

Unfortunately, the road to data strategy success is fraught with challenges, so CIOs and other technology leaders need to plan and execute carefully. Here are some data strategy mistakes IT leaders would be wise to avoid. Overlooking these data resources is a big mistake. It will not be something they can ignore.

Data Strategy 131

Data Strategy Strategy Unstructured Data Data Governance 131

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 56

Data Integration Optimization Software Insurance 56

AWS Big Data

OCTOBER 5, 2023

In today’s data-driven world, the ability to effortlessly move and analyze data across diverse platforms is essential. Amazon AppFlow , a fully managed data integration service, has been at the forefront of streamlining data transfer between AWS services, software as a service (SaaS) applications, and now Google BigQuery.

Data Warehouse 88

Data Warehouse Machine Learning Data Integration Data-driven 88

Smarten

AUGUST 4, 2023

The Right Self-Serve Data Preparation Solution is Sophisticated, Easy-to-Use and Ensures User Adoption! If your team has easy-to-use tools and features, you are much more likely to experience the user adoption you want and to improve data literacy and data democratization across the organization.

Data Lake 52

Data Lake Machine Learning Data Integration Optimization 52

CIO Business Intelligence

JANUARY 9, 2023

Customers are increasingly demanding access to real-time data, and freight transportation provider Estes Express Lines is among the rising tide of enterprises overhauling their data operations to deliver it. While the company had a data warehouse, it was primarily used for analysis.

Data Strategy 109

Data Strategy Strategy Data Governance Marketing 109

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. One of the key benefits of DataOps automation is the ability to speed up the development and deployment of data-driven solutions.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

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. A hybrid ERP environment involves integrating both on-premises and cloud-based systems to manage an organization’s business processes.

Finance 52

Finance Reporting Data Integration Risk 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. We would like to talk about data visualization and its role in the big data movement.

Visualization 135

Visualization Cost-Benefit Big Data Prescriptive Analytics 135

DataKitchen

OCTOBER 25, 2022

Observability is a methodology for providing visibility of every journey that data takes from source to customer value across every tool, environment, data store, team, and customer so that problems are detected and addressed immediately. Data journey observability is the first step in implementing DataOps.

Testing 130

Testing Data-driven Visualization Dashboards 130

Ontotext

MARCH 27, 2024

Both nodes and edges have associated properties modeled as key-values with primitive data types and are single-valued. They also don’t have features for enterprise data management such as schema language, data validation capabilities, interoperable serialization formats, or a proper modeling language. This makes LPGs inflexible.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 105

Data Lake Management Metrics Data Warehouse 105

AWS Big Data

MARCH 3, 2023

Although Tricentis has amassed such data over a decade, the data remains untapped for valuable insights. Each of these tools has its own reporting capabilities that make it difficult to combine the data for integrated and actionable business insights. Finally, data integrity is of paramount importance.

Software 52

Software Data Lake Testing Cost-Benefit 52

CIO Business Intelligence

JUNE 7, 2022

What is data analytics? Data analytics is a discipline focused on extracting insights from data. It comprises the processes, tools and techniques of data analysis and management, including the collection, organization, and storage of data. What are the four types of data analytics? Data analytics tools.

Data Analytics 123

Data Analytics Diagnostic Analytics Management Analytics 123

CIO Business Intelligence

JANUARY 24, 2024

Introduction to Agent Swarms Agent Swarms represent a transformative approach to intelligent automation, drawing inspiration from the collective behaviors of natural entities like bees and ants. Khiyara and Martins’ strategic framework for Agent Swarms unleashes the transformative power of intelligent automation.

IoT 92

IoT Machine Learning Optimization Internet of Things 92

AWS Big Data

MARCH 15, 2023

The API retrieves data at runtime from an Amazon Aurora PostgreSQL-Compatible Edition database for end-user consumption. To populate the database, the Infomedia team developed a data pipeline using Amazon Simple Storage Service (Amazon S3) for data storage, AWS Glue for data transformations, and Apache Hudi for CDC and record-level updates.

Cost-Benefit 68

Cost-Benefit Data Processing Optimization Data-driven 68

Data Virtualization

JULY 20, 2023

Reading Time: < 1 minute In this post, I’m going to cover logical data management and its impact on data mesh architectures. But there’s a lot of confusion in the marketplace today between different types of architectures, specifically data mesh and data fabric, so I’ll.

Management 40

Management Data Integration IT Data Quality 40

Octopai

NOVEMBER 13, 2022

The modern data stack is a data management system built out of cloud-based data systems. A given modern data stack will usually include components for data ingestion from your data sources, data transformation, data storage, data analysis and reporting.

Enterprise 77

Enterprise Data Warehouse Reporting Metadata 77

Alation

JANUARY 17, 2023

Chances are, you’ve heard of the term “modern data stack” before. In this article, I will explain the modern data stack in detail, list some benefits, and discuss what the future holds. It is known to have benefits in handling data due to its robustness, speed, and scalability. Extract, load, Transform (ELT) tools.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

erwin

APRIL 29, 2020

Data lineage is the journey data takes from its creation through its transformations over time. Tracing the source of data is an arduous task. With all these diverse data sources, and if systems are integrated, it is difficult to understand the complicated data web they form much less get a simple visual flow.

Metadata 111

Metadata Data Governance Key Performance Indicator Data Quality 111

AWS Big Data

JULY 25, 2023

In this post, we demonstrate how Talend easily integrates with Redshift Serverless to help you accelerate and scale data analytics with trusted data. About Redshift Serverless Redshift Serverless makes it simple to run and scale analytics without having to manage your data warehouse infrastructure.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

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. AWS Glue is a serverless data integration service that makes it easier to discover, prepare, move, and integrate data from multiple sources for analytics, ML, and application development.

Visualization 99

Visualization Dashboards Data-driven Gap analysis 99

DataKitchen

JANUARY 23, 2023

What is data lineage? Data lineage traces data’s origin, history, and movement through various processing, storage, and analysis stages. It is used to understand the provenance of data and how it is transformed and to identify potential errors or issues. What is missing in data lineage?

Testing 130

Testing Data Governance Data Quality Data-driven 130