DataKitchen

JANUARY 25, 2022

There’s no shortage of consultants who will promise to manage the end-to-end lifecycle of data from integration to transformation to visualization. . The challenge is that data engineering and analytics are incredibly complex. For example, DataOps can be used to automate data integration.

Consulting 244

Consulting Testing Data Lake Data Quality 244

DataKitchen

APRIL 13, 2021

DataOps needs a directed graph-based workflow that contains all the data access, integration, model and visualization steps in the data analytic production process. It orchestrates complex pipelines, toolchains, and tests across teams, locations, and data centers. OwlDQ — Predictive data quality.

Testing 300

Testing Machine Learning Consulting Data Science 300

IBM Big Data Hub

JULY 13, 2023

When we talk about data integrity, we’re referring to the overarching completeness, accuracy, consistency, accessibility, and security of an organization’s data. Together, these factors determine the reliability of the organization’s data. In short, yes.

Data Quality 63

Data Quality Data Integration Metadata Cost-Benefit 63

AWS Big Data

MAY 23, 2024

Hundreds of thousands of organizations build data integration pipelines to extract and transform data. They establish data quality rules to ensure the extracted data is of high quality for accurate business decisions. We also show how to take action based on the data quality results.

Data Quality 101

Data Quality Metrics Data Lake Sales 101

AWS Big Data

DECEMBER 4, 2024

Collaborate and build faster using familiar AWS tools for model development, generative AI, data processing, and SQL analytics with Amazon Q Developer , the most capable generative AI assistant for software development, helping you along the way. Having confidence in your data is key.

Data Analytics 85

Data Analytics Analytics Data Lake Data Quality 85

Smarten

APRIL 25, 2024

How Can I Ensure Data Quality and Gain Data Insight Using Augmented Analytics? There are many business issues surrounding the use of data to make decisions. One such issue is the inability of an organization to gather and analyze data.

Data Quality 64

Data Quality Analytics Machine Learning Visualization 64

DataKitchen

SEPTEMBER 21, 2023

These layers help teams delineate different stages of data processing, storage, and access, offering a structured approach to data management. In the context of Data in Place, validating data quality automatically with Business Domain Tests is imperative for ensuring the trustworthiness of your data assets.

Testing 169

Testing Data Quality Predictive Modeling Metrics 169

AWS Big Data

JANUARY 15, 2025

In addition to real-time analytics and visualization, the data needs to be shared for long-term data analytics and machine learning applications. The data science and AI teams are able to explore and use new data sources as they become available through Amazon DataZone.

IoT 100

IoT Machine Learning Metadata Data-driven 100

AWS Big Data

JUNE 6, 2023

AWS Glue is a serverless data integration service that makes it simple to discover, prepare, and combine data for analytics, machine learning (ML), and application development. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions.

Data Quality 82

Data Quality Data-driven Data Lake Metrics 82

David Menninger's Analyst Perspectives

OCTOBER 8, 2024

Collibra was founded in 2008 by Chief Executive Officer Felix Van de Maele and Chief Data Citizen Stijn Christiaens. Self-service access to data is only truly valuable if users can trust the data they have access to, however. Collibra also announced the acquisition of Husprey in 2023 for its SQL data notebook functionality.

Data Quality 130

Data Quality Data Governance Enterprise Visualization 130

DataKitchen

MAY 10, 2021

A robust process checks source data and work-in-progress at each processing step along the way to polished visualizations, charts, and graphs. Figure 1: The process of transforming raw data into actionable business intelligence is a manufacturing process. It’s not about data quality . It’s not only about the data.

Testing 214

Testing Manufacturing Data Quality Statistics 214

CIO Business Intelligence

MARCH 24, 2023

The Business Application Research Center (BARC) warns that data governance is a highly complex, ongoing program, not a “big bang initiative,” and it runs the risk of participants losing trust and interest over time. Informatica Axon Informatica Axon is a collection hub and data marketplace for supporting programs.

Data Governance 142

Data Governance Management Metadata Data Quality 142

O'Reilly on Data

DECEMBER 12, 2019

Partial dependence, accumulated local effect (ALE), and individual conditional expectation (ICE) plots : this involves systematically visualizing the effects of changing one or more variables in your model. There are a ton of packages for these techniques: ALEPlot , DALEX , ICEbox , iml , and pdp in R; and PDPbox and PyCEbox in Python.

Machine Learning 281

Machine Learning Modeling Testing Risk Management 281

erwin

DECEMBER 9, 2024

And if it isnt changing, its likely not being used within our organizations, so why would we use stagnant data to facilitate our use of AI? The key is understanding not IF, but HOW, our data fluctuates, and data observability can help us do just that. And lets not forget about the controls.

Metadata 52

Metadata Data Quality Sales Modeling 52

BizAcuity

NOVEMBER 13, 2024

Challenges in Achieving Data-Driven Decision-Making While the benefits are clear, many organizations struggle to become fully data-driven. Challenges such as data silos, inconsistent data quality, and a lack of skilled personnel can create significant barriers.

Consulting 52

Consulting Data-driven Cost-Benefit Business Intelligence 52

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. Seeing data pipelines and information flows further supports compliance efforts. Data Quality.

Metadata 111

Metadata Key Performance Indicator Data Governance Data Quality 111

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 101

Metadata Data Lake Visualization Data Quality 101

datapine

FEBRUARY 22, 2022

IT should be involved to ensure governance, knowledge transfer, data integrity, and the actual implementation. Clean data in, clean analytics out. Cleaning your data may not be quite as simple, but it will ensure the success of your BI. Indeed, every year low-quality data is estimated to cost over $9.7

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Dashboards 218

AWS Big Data

JULY 29, 2024

This ensures that each change is tracked and reversible, enhancing data governance and auditability. History and versioning : Iceberg’s versioning feature captures every change in table metadata as immutable snapshots, facilitating data integrity, historical views, and rollbacks.

Metadata 118

Metadata Snapshot Data Lake Metrics 118

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 107

Analytics IT Data Lake Visualization 107

DataKitchen

JUNE 19, 2023

Another way to look at the five pillars is to see them in the context of a typical complex data estate. Using automated data validation tests, you can ensure that the data stored within your systems is accurate, complete, consistent, and relevant to the problem at hand. Data engineers are unable to make these business judgments.

Testing 100

Testing Data Quality Cost-Benefit Metrics 100

erwin

MAY 27, 2020

And it exists across these hybrid architectures in different formats: big and unstructured and traditional structured business data may physically sit in different places. What’s desperately needed is a way to understand the relationships and interconnections between so many entities in data sets in detail.

Modeling 98

Modeling Metadata Data Governance Visualization 98

AWS Big Data

JULY 25, 2024

Migrating workloads to AWS Glue AWS Glue is a serverless data integration service that helps analytics users to discover, prepare, move, and integrate data from multiple sources. With AWS Glue, you can discover and connect to hundreds of different data sources and manage your data in a centralized data catalog.

Visualization 105

Visualization Management Data Integration Testing 105

Ontotext

FEBRUARY 19, 2020

Paradoxically, even without a shared definition and common methodology, the knowledge graph (and its discourse) has steadily settled in the discussion about data management, data integration and enterprise digital transformation. Clean your data to ensure data quality. Maximize the usability of your data.

Modeling 90

Modeling Knowledge Discovery Data Quality Visualization 90

Smarten

JANUARY 30, 2024

Business users cannot even hope to prepare data for analytics – at least not without the right tools. Gartner predicts that, ‘data preparation will be utilized in more than 70% of new data integration projects for analytics and data science.’ So, why is there so much attention paid to the task of data preparation?

Analytics 69

Analytics Visualization Data Quality Metadata 69

AWS Big Data

APRIL 25, 2023

Data and its various uses is increasingly evident in companies, and each professional has their preferences about which technologies to use to visualize data, which isn’t necessarily in line with the technological needs and infrastructure of a company. In this post, we discuss why we chose QuickSight and how we implemented it.

Visualization 52

Visualization IT Data-driven Reporting 52

AWS Big Data

FEBRUARY 29, 2024

However, enterprise data generated from siloed sources combined with the lack of a data integration strategy creates challenges for provisioning the data for generative AI applications. Implement data privacy policies. Implement data quality by data type and source.

Data Governance 109

Data Governance Unstructured Data Metadata Data Lake 109

BI-Survey

FEBRUARY 17, 2020

While compliance is the major driver for data governance, it bears the risk of reducing it to a very restrictive procedure. Data quality is the top challenge when it comes to using data, closely followed by organizational issues. Inadequate data quality remains the foremost challenge users face when using data.

Data Governance 89

Data Governance Data Warehouse Data Quality Data Strategy 89

IBM Big Data Hub

APRIL 27, 2022

The data fabric architectural approach can simplify data access in an organization and facilitate self-service data consumption at scale. Read: The first capability of a data fabric is a semantic knowledge data catalog, but what are the other 5 core capabilities of a data fabric? What’s a data mesh?

Management 79

Management Metadata Data Architecture Data Lake 79

AWS Big Data

MARCH 26, 2024

A Gartner Marketing survey found only 14% of organizations have successfully implemented a C360 solution, due to lack of consensus on what a 360-degree view means, challenges with data quality, and lack of cross-functional governance structure for customer data.

Data Strategy 78

Data Strategy Strategy Data Warehouse Prescriptive Analytics 78

CIO Business Intelligence

JUNE 29, 2022

MuleSoft’s historic strength is in data integration and API management: enterprises such as Decathlon and REA Group use its Anypoint Platform to build modular systems and automate critical business processes. We’re improving data quality and accessibility and enabling our business to use the data strategically and at scale,” she said.

Data Quality 97

Data Quality Sales Visualization Enterprise 97

Octopai

JANUARY 31, 2021

Another podcast we think is worth a listen is Agile Data. Throughout each episode, hosts Shane and Nigel discuss how to incorporate agile techniques when teams deliver analytics, data, and visualizations. Topics they chat about include: going serverless, data layers, and how to adapt for a “BI Lifecycle.”

Data Governance 83

Data Governance Data Processing Data Quality Metadata 83

Octopai

MAY 15, 2023

By analyzing this information, organizations can optimize their infrastructure and storage strategies, avoiding unnecessary storage costs and efficiently allocating resources based on data usage patterns. Data integration and ETL costs: Large organizations often deal with complex data integration and Extract, Transform, Load (ETL) processes.

Data Quality 52

Data Quality Data Governance Data Integration Risk 52

Octopai

JUNE 26, 2020

Data governance tools are available to help ensure availability, usability, consistency, data integrity and data security. This helps establish clear processes for effective data management throughout the enterprise. The data journey governed.

Metadata 98

Metadata Data Governance Enterprise Reporting 98

Jedox

FEBRUARY 13, 2020

The power of artificial intelligence (AI) lies within its ability to make sense of large amounts of data. For the increasing support of planning, budgeting and controlling processes through advanced analytics and AI solutions, powerful data management and data integration are an indispensable prerequisite.

Forecasting 58

Forecasting Predictive Analytics Sales Data Integration 58

IBM Big Data Hub

MAY 9, 2022

These use cases provide a foundation that delivers a rich and intuitive data shopping experience. This data marketplace capability will enable organizations to efficiently deliver high quality governed data products at scale across the enterprise. Multicloud data integration. million each year [1] and $1.2

Management 56

Management Data Quality Metadata Data Integration 56

Alation

MAY 16, 2023

Data Pipeline Use Cases Here are just a few examples of the goals you can achieve with a robust data pipeline: Data Prep for Visualization Data pipelines can facilitate easier data visualization by gathering and transforming the necessary data into a usable state.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69