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 94

Analytics IT Data Lake Visualization 94

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

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 130

Testing Cost-Benefit Metrics Data Quality 130

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

FineReport

APRIL 9, 2024

The integration of AI and machine learning into BI tools is revolutionizing the processing and analysis of data, propelling organizations toward more accurate forecasting and proactive decision-making. In addition to these advancements, another prominent trend in data analysis is the growing impact of data visualization.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 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 93

Data Governance Unstructured Data Metadata Data Lake 93

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 Data Governance Key Performance Indicator Data Quality 111

FineReport

MAY 31, 2023

A financial dashboard, one of the most important types of data dashboards , functions as a business intelligence tool that enables finance and accounting teams to visually represent, monitor, and present financial key performance indicators (KPIs). Inaccurate or inconsistent data can lead to erroneous conclusions and decisions.

Dashboards 52

Dashboards Key Performance Indicator Metrics Visualization 52

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 57

Management Data Quality Metadata Data Integration 57

IBM Big Data Hub

DECEMBER 16, 2022

An enterprise data catalog does all that a library inventory system does – namely streamlining data discovery and access across data sources – and a lot more. For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

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

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 73

Data Quality Data Lake Data-driven Metrics 73

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 57

Data Governance Data Processing Data Quality Metadata 57

Ontotext

SEPTEMBER 15, 2020

Added to this is the increasing demands being made on our data from event-driven and real-time requirements, the rise of business-led use and understanding of data, and the move toward automation of data integration, data and service-level management. This provides a solid foundation for efficient data integration.

Metadata 69

Metadata Knowledge Discovery Data Quality Strategy 69

Alation

JUNE 2, 2022

How Data Lineage Is a Use Case in ML. Data lineage is one example of a use case in which ML can play a pivotal role. Data lineage is the process of recording and visualizing data flowing from data sources to consumption. Data lineage allows companies to troubleshoot errors in data processes.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

FineReport

APRIL 26, 2023

Having visually appealing graphics can also increase user adoption. Advanced analytics capabilities : The tool should be able to analyze data and identify patterns, as well as forecast future events with complex forecasting algorithms, going beyond simple mathematical calculations.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

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 176

Testing Data Quality Predictive Modeling Metrics 176

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 191

Machine Learning Modeling Testing Risk Management 191

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 84

Metadata Data Governance Enterprise Reporting 84

CIO Business Intelligence

SEPTEMBER 2, 2022

Finance companies collect massive amounts of data, and data engineers are vital in ensuring that data is maintained and that there’s a high level of data quality, efficiency, and reliability around data collection.

Finance 98

Finance IT Software Reporting 98

CIO Business Intelligence

AUGUST 31, 2022

Finance companies collect massive amounts of data, and data engineers are vital in ensuring that data is maintained and that there’s a high level of data quality, efficiency, and reliability around data collection.

Finance 98

Finance IT Software Reporting 98

Ontotext

MARCH 8, 2023

Yet, the biggest challenge for risk analysis continues to suffer from lack of a scalable way of understanding how data is interrelated. A graph or network is enabling institutions to model and visualize these connections as a collection of nodes and points that specifies the exact link between certain financial concepts and entities.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

Howard Dresner

JANUARY 20, 2014

Examples: user empowerment and the speed of getting answers (not just reports) • There is a growing interest in data that tells stories; keep up with advances in storyboarding to package visual analytics that might fill some gaps in communication and collaboration • Monitor rumblings about trend to shift data to secure storage outside the U.S.

Business Intelligence 56

Business Intelligence Software Data Processing Marketing 56

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

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 307

Testing Machine Learning Consulting Data Quality 307

CIO Business Intelligence

FEBRUARY 20, 2023

To earn the Salesforce Data Architect certification , candidates should be able to design and implement data solutions within the Salesforce ecosystem, such as data modelling, data integration and data governance.

Consulting 64

Consulting B2B Cost-Benefit Sales 64

Smarten

APRIL 19, 2024

The value of an AI-focused analytics solution can only be fully realized when a business has ensured data quality and integration of data sources, so it will be important for businesses to choose an analytics solution and service provider that can help them achieve these goals.

Analytics 57

Analytics Predictive Modeling KPI Machine Learning 57

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 67

Data Strategy Strategy Data Warehouse Prescriptive Analytics 67

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

Alation

SEPTEMBER 22, 2022

Alation is pleased to launch a new strategic partnership with Fivetran, the leader in modern data integration. This new partnership will unify governed, quality data into a single view, granting all stakeholders total visibility into pipelines and providing them with a superior ability to make data-driven decisions.

Metadata 52

Metadata Data-driven Data Quality Visualization 52

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 88

Management Metadata Data Architecture Data Lake 88

FineReport

MAY 25, 2023

An HR dashboard functions as an advanced analytics tool that utilizes interactive data visualizations to present crucial HR metrics. Similar to various other business departments, human resources is gradually transforming into a data-centric function. This helps in preventing errors and maintaining data quality.

Dashboards 52

Dashboards Metrics Cost-Benefit Key Performance Indicator 52

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 40

Data Lake Data Governance Data Warehouse Data Processing 40

FineReport

JULY 18, 2022

The features you or your company need are core factors influencing your selection of the data analytics tool. For example, if you want the features of data visualization , such as stunning dashboards and rich charts, business intelligence tools are more suitable for you than a pure programming tool. Free Download. From FineBI.

Forecasting 52

Forecasting Dashboards Visualization Statistics 52

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

Ontotext

JANUARY 6, 2022

That is why we have used GraphDB , Ontotext Platform and our significant expertise in semantic data integration to show how we can improve the quality of ENTSO-E Transparency data and develop flexible analytics by leveraging the knowledge graph approach. Spotting Data Consistency Issues. Let’s take a closer look.

Marketing 52

Marketing Data Quality Dashboards Visualization 52

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 Technology 90