CIO Business Intelligence

MAY 21, 2024

In the annual Porsche Carrera Cup Brasil, data is essential to keep drivers safe and sustain optimal performance of race cars. Until recently, getting at and analyzing that essential data was a laborious affair that could take hours, and only once the race was over.

Broadcasting 125

Broadcasting Recreation/Entertainment Manufacturing Data Lake 125

IBM Big Data Hub

MAY 9, 2023

Data: the foundation of your foundation model Data quality matters. An AI model trained on biased or toxic data will naturally tend to produce biased or toxic outputs. When objectionable data is identified, we remove it, retrain the model, and repeat. Data curation is a task that’s never truly finished.

Enterprise 128

Enterprise Technology Modeling Cost-Benefit 128

Timo Elliott

JANUARY 3, 2022

It’s stored in corporate data warehouses, data lakes, and a myriad of other locations – and while some of it is put to good use, it’s estimated that around 73% of this data remains unexplored. Improving data quality. Unexamined and unused data is often of poor quality. Data augmentation.

IT 143

IT Unstructured Data Data Quality Machine Learning 143

Timo Elliott

DECEMBER 14, 2022

The future is enabled by technology, but it’s not about the technical infrastructures: it’s about optimizing end-to-end processes, business capabilities, and business ecosystems. You lose the roots: the metadata, the hierarchies, the security, the business context of the data. So how do organizations do that? Business Context.

Data Lake 105

Data Lake Recreation/Entertainment Metadata Data Warehouse 105

AWS Big Data

JUNE 6, 2023

In this post we showcase how we used AWS Glue to move siloed digital analytics data, with inconsistent arrival times, to AWS S3 (our Data Lake) and our central data warehouse (DWH), Snowflake. AWS Glue gave us a cost-efficient option to migrate the data and we further optimized storage cost by pruning cold data.

Analytics 55

Analytics Data Lake Testing Optimization 55

CIO Business Intelligence

FEBRUARY 16, 2023

Selling the value of data transformation Iyengar and his team are 18 months into a three- to five-year journey that started by building out the data layer — corralling data sources such as ERP, CRM, and legacy databases into data warehouses for structured data and data lakes for unstructured data.

Unstructured Data 104

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 104

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. Comprehensive search and access to relevant data.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

AWS Big Data

MARCH 7, 2023

Flexible and easy to use – The solutions should provide less restrictive, easy-to-access, and ready-to-use data. They should also provide optimal performance with low or no tuning. A data hub contains data at multiple levels of granularity and is often not integrated. Data repositories represent the hub.

Analytics 72

Analytics Data Warehouse Data Lake Metadata 72

DataKitchen

DECEMBER 9, 2022

Observability in DataOps refers to the ability to monitor and understand the performance and behavior of data-related systems and processes, and to use that information to improve the quality and speed of data-driven decision making. Overall, DataOps observability is an essential component of modern data-driven organizations.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy. The best way to drive value is through use cases.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

CIO Business Intelligence

APRIL 29, 2022

This would be straightforward task were it not for the fact that, during the digital-era, there has been an explosion of data – collected and stored everywhere – much of it poorly governed, ill-understood, and irrelevant. Further, data management activities don’t end once the AI model has been developed. Addressing the Challenge.

Data Governance 145

Data Governance IT Risk Data Lake 145

DataKitchen

NOVEMBER 18, 2022

In addition to the tracking of relationships and quality metrics, DataOps Observability journeys allow users to establish baselines?concrete concrete expectations for run schedules, run durations, data quality, and upstream and downstream dependencies. And she’ll know when newer data will arrive.

Testing 130

Testing Statistics Measurement Metrics 130

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 85

Enterprise Data Warehouse Snapshot Cost-Benefit 85

AWS Big Data

JUNE 6, 2023

You can use AWS Glue to create, run, and monitor data integration and ETL (extract, transform, and load) pipelines and catalog your assets across multiple data stores. Hundreds of thousands of customers use data lakes for analytics and ML to make data-driven business decisions.

Data Quality 76

Data Quality Data Lake Data-driven Metrics 76

FineReport

MARCH 24, 2024

Data analysts leverage four key types of analytics in their work: Prescriptive analytics: Advising on optimal actions in specific scenarios. Data Analyst Job Description: Major Tasks and Duties Data analysts collaborate with management to prioritize information needs, collect and interpret business-critical data, and report findings.

Statistics 52

Statistics Data mining Visualization Reporting 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 120

Cost-Benefit Internet of Things Data-driven Data Lake 120

bridgei2i

MARCH 11, 2021

Creating an efficient data governance strategy means – Breaking down all sources of accumulated data across the organization. Recognizing the “right” data that can be optimized by AI-powered business analytics tools. Identify data errors and eliminate them from the system. in the system.

Key Performance Indicator 52

Key Performance Indicator Data Governance Data Lake Metadata 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 89

Data Lake Analytics Snapshot Optimization 89

AWS Big Data

FEBRUARY 1, 2023

With data volumes exhibiting a double-digit percentage growth rate year on year and the COVID pandemic disrupting global logistics in 2021, it became more critical to scale and generate near-real-time data. This introduces the need for both polling and pushing the data to access and analyze in near-real time.

Optimization 52

Optimization Forecasting Data Lake Metadata 52

Alation

JANUARY 26, 2023

Offer the right tools Data stewardship is greatly simplified when the right tools are on hand. So ask yourself, does your steward have the software to spot issues with data quality, for example? 2) Always Remember Compliance Source: Unsplash There are now many different data privacy and security laws worldwide.

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

AWS Big Data

JULY 13, 2023

Data quality for account and customer data – Altron wanted to enable data quality and data governance best practices. Goals – Lay the foundation for a data platform that can be used in the future by internal and external stakeholders.

Optimization 91

Optimization B2B Data Quality Sales 91

Ontotext

MARCH 8, 2023

Here, I will draw upon our own experience from client projects and lessons learned to provide a selection of optimal use cases for knowledge graphs and semantic solutions along with real world examples of their applications. For many organizations, however, the question remains, “Is it the right solution for us?”

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52

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 117

Data Lake Unstructured Data Data Warehouse Data Quality 117

Cloudera

MARCH 28, 2024

And of those organizations working on some stage of AI adoption, a few of the top benefits included increased productivity (35%), enhanced operational efficiency (33%), improved customer experience (33%), and optimized supply chain and logistics (33%). The benefits are clear, and there’s plenty of potential that comes with AI adoption.

Data Architecture 97

Data Architecture Strategy Data Lake Data-driven 97

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

BizAcuity

APRIL 14, 2022

Big Data technology in today’s world. Did you know that the big data and business analytics market is valued at $198.08 Or that the US economy loses up to $3 trillion per year due to poor data quality? quintillion bytes of data which means an average person generates over 1.5 megabytes of data every second?

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

Alation

MAY 16, 2023

What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The various steps along the pipeline involve transforming, optimizing, cleaning, filtering, integrating, and aggregating the data. The end result is data that is ready to be analyzed.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

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 69

Data Strategy Strategy Data Warehouse Prescriptive Analytics 69

IBM Big Data Hub

DECEMBER 7, 2023

This siloed approach often resulted in data redundancy and complexity, hampering integration with other business systems. C-OLAP optimized data storage for faster query processing, while IM-OLAP stored data in memory to minimize data access latency and enable real-time analytics.

OLAP 58

OLAP Slice and Dice Cost-Benefit Data Warehouse 58

Alation

MAY 16, 2023

What is a Data Pipeline? A data pipeline is a series of processing steps that move data from its source to its destination. The various steps along the pipeline involve transforming, optimizing, cleaning, filtering, integrating, and aggregating the data. The end result is data that is ready to be analyzed.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

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. With Netezza support for 1.2

Cost-Benefit 76

Cost-Benefit Metadata Optimization Management 76

IBM Big Data Hub

OCTOBER 12, 2023

To maximize the business outcomes that can come from using AI while also controlling costs and reducing inherent AI complexities, organizations need to combine AI-optimized data storage capabilities with a data governance program exclusively made for AI. But the implementation of AI is only one piece of the puzzle.

Cost-Benefit 77

Cost-Benefit Metadata Data Governance Modeling 77

Alation

MARCH 21, 2023

What are common data challenges for the travel industry? Some companies struggle to optimize their data’s value and leverage analytics effectively. When companies lack a data governance strategy , they may struggle to identify all consumer data or flag personal data as subject to compliance audits.

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52

Ontotext

FEBRUARY 26, 2024

Firstly, on the data maturity spectrum, the vast majority of organizations I’ve spoken with are stuck in the information stage. They have massive amounts of data they’re collecting and storing in their relational databases, document stores, data lakes, and data warehouses. Let’s summarize very quickly.

Technology 52

Technology Cost-Benefit Data-driven Metadata 52

Cloudera

AUGUST 4, 2021

Factors such as siloed platforms and the absence of centralized data stewardship all regularly contribute to a lack of data visibility. . Organizations are facing a data tsunami with more data being generated than ever, making it even more difficult to discover, catalog, and keep track of all this information.

Data Governance 89

Data Governance Metadata Data-driven Enterprise 89

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

Cloudera

SEPTEMBER 6, 2022

Previously, there were three types of data structures in telco: . Entity data sets — i.e. marketing data lakes . There are three major architectures under the modern data architecture umbrella. . Optimization Data lakehouse is the platform wherein the data assets reside.

Data Architecture 87

Data Architecture Cost-Benefit Digital Transformation Business Driver 87