IBM Big Data Hub

DECEMBER 16, 2022

For example, data catalogs have evolved to deliver governance capabilities like managing data quality and data privacy and compliance. It uses metadata and data management tools to organize all data assets within your organization. After all, Alex may not be aware of all the data available to her.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

CIO Business Intelligence

SEPTEMBER 8, 2022

In Foundry’s 2022 Data & Analytics Study , 88% of IT decision-makers agree that data collection and analysis have the potential to fundamentally change their business models over the next three years. The ability to pivot quickly to address rapidly changing customer or market demands is driving the need for real-time data.

Cost-Benefit 108

Cost-Benefit Internet of Things Data-driven Data Lake 108

AWS Big Data

MARCH 7, 2023

It covers how to use a conceptual, logical architecture for some of the most popular gaming industry use cases like event analysis, in-game purchase recommendations, measuring player satisfaction, telemetry data analysis, and more. A data hub contains data at multiple levels of granularity and is often not integrated.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

CIO Business Intelligence

APRIL 29, 2022

Software development, once solely the domain of human programmers, is now increasingly the by-product of data being carefully selected, ingested, and analysed by machine learning (ML) systems in a recurrent cycle. Further, data management activities don’t end once the AI model has been developed. era is upon us.

Data Governance 143

Data Governance IT Risk Data Lake 143

Jedox

OCTOBER 22, 2020

In addition to using data to inform your future decisions, you can also use current data to make immediate decisions. Some of the technologies that make modern data analytics so much more powerful than they used t be include data management, data mining, predictive analytics, machine learning and artificial intelligence.

Data Analytics 69

Data Analytics Analytics Unstructured Data Data mining 69

FineReport

MARCH 24, 2024

Data analysts contribute value to organizations by uncovering trends, patterns, and insights through data gathering, cleaning, and statistical analysis. They collaborate with cross-functional teams to meet organizational objectives and work across diverse sectors, including business intelligence, finance, marketing, and consulting.

Statistics 52

Statistics Data mining Visualization Reporting 52

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Overlapping with the above, from around 2012, I began to get involved in also designing and implementing Big Data Architectures; initially for narrow purposes and later Data Lakes spanning entire enterprises.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 83

Enterprise Data Warehouse Snapshot Cost-Benefit 83

Alation

JANUARY 26, 2023

That’s why many organizations invest in technology to improve data processes, such as a machine learning data pipeline. However, data needs to be easily accessible, usable, and secure to be useful — yet the opposite is too often the case. Without proper quality control, data inaccuracies are more likely to occur.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

Alation

OCTOBER 21, 2021

Data Swamp vs Data Lake. When you imagine a lake, it’s likely an idyllic image of a tree-ringed body of reflective water amid singing birds and dabbling ducks. I’ll take the lake, thank you very much. But when it’s dirty, stagnant, or hard to unleash, your business will suffer. Benefits of a Data Lake.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

AWS Big Data

JULY 20, 2023

With data becoming the driving force behind many industries today, having a modern data architecture is pivotal for organizations to be successful. In this post, we describe Orca’s journey building a transactional data lake using Amazon Simple Storage Service (Amazon S3), Apache Iceberg, and AWS Analytics.

Data Lake 85

Data Lake Analytics Snapshot Optimization 85

AWS Big Data

MAY 7, 2024

It also makes it easier for engineers, data scientists, product managers, analysts, and business users to access data throughout an organization to discover, use, and collaborate to derive data-driven insights. Note that a managed data asset is an asset for which Amazon DataZone can manage permissions.

Metadata 74

Metadata Data Lake Data Processing Data-driven 74

CIO Business Intelligence

MARCH 9, 2022

However, they do contain effective data management, organization, and integrity capabilities. As a result, users can easily find what they need, and organizations avoid the operational and cost burdens of storing unneeded or duplicate data copies. On the other hand, they don’t support transactions or enforce data quality.

Data Lake 101

Data Lake Unstructured Data Data Warehouse Data Quality 101

AWS Big Data

JULY 13, 2023

This post discusses the journey that took Altron from their initial goals, to technical implementation, to the business value created from understanding their customers and their unique opportunities better. Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices.

Optimization 88

Optimization B2B Data Quality Sales 88

CIO Business Intelligence

DECEMBER 21, 2022

Every day, organizations of every description are deluged with data from a variety of sources, and attempting to make sense of it all can be overwhelming. So a strong business intelligence (BI) strategy can help organize the flow and ensure business users have access to actionable business insights. “By

IT 127

IT Business Intelligence Sales Key Performance Indicator 127

Cloudera

AUGUST 30, 2022

For state and local agencies, data silos create compounding problems: Inaccessible or hard-to-access data creates barriers to data-driven decision making. Legacy data sharing involves proliferating copies of data, creating data management, and security challenges. Towards Data Science ). Forrester ).

Data Architecture 76

Data Architecture Data Lake Metadata Data Warehouse 76

Alation

JULY 19, 2022

Across the country, data scientists have an unemployment rate of 2% and command an average salary of nearly $100,000. As they attempt to put machine learning models into production, data science teams encounter many of the same hurdles that plagued data analytics teams in years past: Finding trusted, valuable data is time-consuming.

Metadata 59

Metadata Data Quality Statistics Data Science 59

IBM Big Data Hub

DECEMBER 7, 2023

Here’s an overview of the key characteristics: AI-powered analytics : Integration of AI and machine learning capabilities into OLAP engines will enable real-time insights, predictive analytics and anomaly detection, providing businesses with actionable insights to drive informed decisions.

OLAP 63

OLAP Slice and Dice Cost-Benefit Data Warehouse 63

CIO Business Intelligence

NOVEMBER 28, 2023

With each game release and update, the amount of unstructured data being processed grows exponentially, Konoval says. This volume of data poses serious challenges in terms of storage and efficient processing,” he says. To address this problem RetroStyle Games invested in data lakes. Quality is job one.

Unstructured Data 122

Unstructured Data Data-driven Visualization Data Quality 122

CIO Business Intelligence

MARCH 22, 2022

Which type(s) of storage consolidation you use depends on the data you generate and collect. . One option is a data lake—on-premises or in the cloud—that stores unprocessed data in any type of format, structured or unstructured, and can be queried in aggregate. Set up unified data governance rules and processes.

Analytics 96

Analytics Key Performance Indicator Data Warehouse Data-driven 96

IBM Big Data Hub

MARCH 14, 2024

Businesses face significant hurdles when preparing data for artificial intelligence (AI) applications. The existence of data silos and duplication, alongside apprehensions regarding data quality, presents a multifaceted environment for organizations to manage.

Cost-Benefit 83

Cost-Benefit Metadata Optimization Management 83

datapine

AUGUST 29, 2022

James Warren, on the other part, is a successful analytics architect with a background in machine learning and scientific computing. 5) Data Analytics Made Accessible, by Dr. Anil Maheshwari. Best for : the new intern who has no idea what data science even means. Stein Kretsinger, founding executive, Advertising.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

Peter James Thomas

MAY 3, 2019

The flip side is that making the necessary investments to provide even basic information has been at the heart of the successful business turnarounds that I have been involved in. The bulk of Business Intelligence efforts would also fall into this area, but there is some overlap with the area I next describe as well.

Strategy 55

Strategy Data Architecture Data Quality Data Strategy 55

IBM Big Data Hub

OCTOBER 12, 2023

They’re built on machine learning algorithms that create outputs based on an organization’s data or other third-party big data sources. Sometimes, these outputs are biased because the data used to train the model was incomplete or inaccurate in some way.

Cost-Benefit 83

Cost-Benefit Metadata Data Governance Modeling 83

Alation

MARCH 21, 2023

Having been in business for over 50 years, ARC had accumulated a massive amount of data that was stored in siloed, on-premises servers across its 7 business domains. Using Alation, ARC automated the data curation and cataloging process. “So

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Domino Data Lab

JUNE 15, 2021

At a certain point, as the demand keeps growing, the data volumes rapidly increase. Data is no longer stored in CSV files, but in a dedicated, purpose built data lake / data warehouse. Existing preprocessing, data ingestion, and data quality processes can be converted from Java/Spark into Java UDFs.

Modeling 69

Modeling Data Science Data-driven Data Warehouse 69

Ontotext

AUGUST 4, 2023

This logical data architecture is designed to help organizations deal with growing volumes of data, spanning data silos with seamless connectivity and a knowledge layer. Using metadata, machine learning (ML), and automation, a data fabric provides a unified view of enterprise data across data formats and locations.

Metadata 52

Metadata Data-driven Data Architecture Data Quality 52

AWS Big Data

MAY 1, 2024

Responsibilities include: Look for the data to be used from the technical data catalog and request access to the data. Handle the process and conversion of data into a format suitable for their own use (such as fact-dimension) with granted referencing permissions. It is crucial in data governance and data management.

Dashboards 111

Dashboards Data-driven Publishing Cost-Benefit 111

IBM Big Data Hub

AUGUST 4, 2023

By leveraging data services and APIs, a data fabric can also pull together data from legacy systems, data lakes, data warehouses and SQL databases, providing a holistic view into business performance. Then, it applies these insights to automate and orchestrate the data lifecycle.

Data Architecture 64

Data Architecture Data Lake Machine Learning Data Governance 64

AWS Big Data

APRIL 5, 2023

The company decided to use AWS to unify its business intelligence (BI) and reporting strategy for both internal organization-wide use cases and in-product embedded analytics targeted at its customers. In this post, we share how Showpad used QuickSight to streamline data and insights access across teams and customers.

Dashboards 52

Dashboards Reporting Cost-Benefit Visualization 52

Jet Global

MAY 9, 2024

Data pipelines are designed to automate the flow of data, enabling efficient and reliable data movement for various purposes, such as data analytics, reporting, or integration with other systems. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

FEBRUARY 23, 2024

The quick and dirty definition of data mapping is the process of connecting different types of data from various data sources. Data mapping is a crucial step in data modeling and can help organizations achieve their business goals by enabling data integration, migration, transformation, and quality.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52