CIO Business Intelligence

JULY 13, 2022

Over the last decade, we have often heard about the proliferation of data creating sources (mobile applications, laptops, sensors, enterprise apps) in heterogeneous environments (cloud, on-prem, edge) resulting in the exponential growth of data being created.

Enterprise 83

Enterprise Data Lake Data Collection Data-driven 83

Cloudera

JUNE 9, 2022

From origin through all points of consumption both on-prem and in the cloud, all data flows need to be controlled in a simple, secure, universal, scalable, and cost-effective way. controlling distribution while also allowing the freedom and flexibility to deliver the data to different services is more critical than ever. .

Data Collection 89

Data Collection IoT Data Lake Unstructured Data 89

Ontotext

FEBRUARY 12, 2024

Now it’s time to hold your domain owners and data producers responsible for data quality and treat data assets as products to be delivered to the organization. Each team should be accountable for providing their prepared data sets to downstream systems. uses its data lake via data mesh to determine wholesale credit risk.

Data Quality 69

Data Quality Data-driven Data Lake Data Governance 69

CIO Business Intelligence

SEPTEMBER 8, 2022

Most organizations understand the profound impact that data is having on modern business. 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.

Cost-Benefit 117

Cost-Benefit Internet of Things Data-driven Data Lake 117

Cloudera

SEPTEMBER 15, 2021

Without them, data collected by IoT sensors, cameras and other devices would have to travel to a data center located hundreds or thousands of miles away. In such a scenario, data latency is essentially unavoidable — and, when real-time action is required, inadmissible. Real-time Demands. Scalability Requirements.

IoT 117

IoT Analytics Internet of Things Data Lake 117

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.

Data Governance 145

Data Governance IT Risk Data Lake 145

Cloudera

APRIL 20, 2022

However, consider all the data collection, merging, analyzing and storing this simple interaction requires; it’s not so simple. Data needs to be stored for treatment, drug interactions and/or allergies, patient records, compliance, pharmacy, payment and insurance purposes.

Insurance 96

Insurance Measurement Data Lake Risk 96

AWS Big Data

DECEMBER 5, 2023

The counties that are in lighter shades represent limited survey responses and need to be included in the targeted data collection strategy. Finally, the dashboard’s user-friendly interface made survey data more accessible to a wider range of stakeholders. The first image shows the dashboard without any active filters.

Measurement 82

Measurement Dashboards Data Warehouse Analytics 82

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 84

Data Science Data Analytics Prescriptive Analytics Analytics 84

CDW Research Hub

APRIL 18, 2022

The complexity and cost of SIEM solutions and the number of resources that security consumes can easily swallow a large portion of an enterprise’s budget, causing many organizations to fall behind in the security data race. Security data lakes can reduce organizations’ reliance on SIEM solutions.

Data Lake 75

Data Lake Enterprise Data Collection Risk 75

CIO Business Intelligence

JULY 12, 2023

P&G engineers developed a high-speed data collection system to capture data to use for training AI models. One challenge they faced is that, while production errors are extremely costly and disruptive, they don’t happen often, which means that failure events are underrepresented in the training data.

Manufacturing 98

Manufacturing Cost-Benefit Data Lake Optimization 98

FineReport

MARCH 24, 2024

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. Certified Analytics Professional (CAP) , providing advanced insights into converting data into actionable insights.

Statistics 52

Statistics Data mining Visualization Reporting 52

Cloudera

JANUARY 24, 2022

Working with Cloudera, Keck created a data lake that eliminated manual data collection errors and gave visibility organization-wide. Doctors often prescribe these powerful painkillers after surgery or to treat chronic debilitating conditions.

Data Lake 65

Data Lake Risk Machine Learning Data Collection 65

Alation

FEBRUARY 13, 2020

Figure 1 illustrates the typical metadata subjects contained in a data catalog. Figure 1 – Data Catalog Metadata Subjects. Datasets are the files and tables that data workers need to find and access. They may reside in a data lake, warehouse, master data repository, or any other shared data resource.

Metadata 64

Metadata Data Lake Recreation/Entertainment Big Data 64

bridgei2i

MARCH 11, 2021

With improved data cataloging functionality, their systems can become responsive. It’ll become easier to store metadata (data lakes, warehouses, data quality systems, etc.) Over time, as more data is constantly fed to the responsive system, ML algorithms improve their efficiency. in the system.

Key Performance Indicator 52

Key Performance Indicator Data Governance Data Lake Metadata 52

Ontotext

NOVEMBER 16, 2023

In a data mesh, domains are represented by a node, which can be an operational data store (ODS), a data warehouse, or a data lake tailored to the domain’s requirements. Don’t Forget Team Structure Team and organizational structure are an important aspect to consider for data mesh.

Metadata 52

Metadata Data-driven Data Quality Data Architecture 52

Alation

FEBRUARY 13, 2020

Today, we’re announcing that Alation has closed a $50 million Series C funding led by Sapphire Ventures, with participation from new investor Salesforce Ventures and our existing investors Costanoa Ventures, DCVC (Data Collective), Harmony Partners and Icon Ventures.

Enterprise 52

Enterprise Data Lake Machine Learning Data-driven 52

Alation

JANUARY 26, 2023

Below are some examples of common data governance goals: All data collection, storage, and usage must meet the terms of legislation. Avoid fines that could result from issues such as data leakage or lack of data minimization practices. This is “table stakes” for any data governance program!).

Data Governance 52

Data Governance Strategy Data Quality Marketing 52

Alation

FEBRUARY 20, 2020

More than any other advancement in analytic systems over the last 10 years, Hadoop has disrupted data ecosystems. By dramatically lowering the cost of storing data for analysis, it ushered in an era of massive data collection. You did not have to understand or prepare the data to get it into Hadoop, so people rarely did.

Data Lake 52

Data Lake Metadata Structured Data Big Data 52

Smart Data Collective

OCTOBER 26, 2019

Big Data Storage Concerns. Large data lakes can take up a massive amount of space, and for off-site storage, this can be a significant concern in cost. Additionally, having a data storage of such magnitude off-site could potentially result in hefty transport fees if the off-site location is far away.

Big Data 44

Big Data Data Lake Cost-Benefit Measurement 44

Cloudera

FEBRUARY 16, 2022

Each workspace is associated with a collection of cloud resources. In the case of CDP Public Cloud, this includes virtual networking constructs and the data lake as provided by a combination of a Cloudera Shared Data Experience (SDX) and the underlying cloud storage. The highest level construct in CML is a workspace.

Machine Learning 82

Machine Learning Modeling Metadata Recreation/Entertainment 82

Alation

FEBRUARY 20, 2020

For many enterprises, a hybrid cloud data lake is no longer a trend, but becoming reality. Due to these needs, hybrid cloud data lakes emerged as a logical middle ground between the two consumption models. earthquake, flood, or fire), where the data collected does not need to be as tightly controlled.

Data Lake 52

Data Lake ROI Metadata Cost-Benefit 52

AWS Big Data

JULY 3, 2023

Terminology Let’s first discuss some of the terminology used in this post: Research data lake on Amazon S3 – A data lake is a large, centralized repository that allows you to manage all your structured and unstructured data at any scale. This is where the tagging feature in Apache Iceberg comes in handy.

Snapshot 84

Snapshot Data Lake Testing Strategy 84

BizAcuity

MARCH 1, 2019

At the backend, based on the data collected, data is stored in data lakes. Such data is collected from hundreds, thousands and millions of users. Then AI/ML algorithms are run on this collected data.

IoT 56

IoT Internet of Things Big Data Data-driven 56

Sisense

APRIL 26, 2020

In our modern digital world, proper use of data can play a huge role in a business’s success. Datasets are exploding at an ever-accelerating rate, so collecting and analyzing data to maximum effect is crucial. Companies and businesses focus a lot on data collection in order to make sure they can get valuable insights out of it.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

Cloudera

MAY 9, 2023

New Data Lakehouse Enables Stronger Data Governance SoftBank needed to reduce the number of workloads on its existing platform and decided to adopt Cloudera to build a data lake capable of managing data more effectively. Team members with various Cloudera capabilities provided 24-hour support for upgrade.

Data Lake 88

Data Lake IoT Data Governance Data Strategy 88

Cloudera

AUGUST 30, 2022

Data Lakehouse: Data lakehouses integrate and unify the capabilities of data warehouses and data lakes, aiming to support artificial intelligence, business intelligence, machine learning, and data engineering use cases on a single platform. Towards Data Science ). Forrester ). Gartner ).

Data Architecture 77

Data Architecture Data Lake Metadata Data Warehouse 77

AWS Big Data

MARCH 26, 2024

In this post, we discuss how you can use purpose-built AWS services to create an end-to-end data strategy for C360 to unify and govern customer data that address these challenges. We recommend building your data strategy around five pillars of C360, as shown in the following figure.

Data Strategy 68

Data Strategy Strategy Data Warehouse Prescriptive Analytics 68

Alation

MAY 16, 2023

Sources can include analytics data regarding user behavior, transactional data from ecommerce websites, and third-party data from other organizations. It’s worth noting that a data pipeline may have more than one data source. Ingestion tools are connected to various data sources.

Data Lake 69

Data Lake Data Governance Data Warehouse Data Processing 69

Cloudera

JANUARY 21, 2021

Storing data in a proprietary, single-workload solution also recreates dangerous data silos all over again, as it locks out other types of workloads over the same shared data. The Data Lake service in Cloudera’s Data Platform provides a central place to understand, manage, secure, and govern data assets across the enterprise.

Data Lake 93

Data Lake Data Warehouse IT Analytics 93

CIO Business Intelligence

JANUARY 30, 2024

Only a few enterprises have adopted fully automated ESG data collection and monitoring tools; the majority still depend on unreliable manual practices,” Everest’s Narayanan says. From there, CIOs can determine the most relevant pieces of data and how to source and automate the gathering of that data, IDC’s Cravens says.

Reporting 111

Reporting Data Quality Strategy Data-driven 111

Peter James Thomas

AUGUST 29, 2018

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

CIO Business Intelligence

SEPTEMBER 22, 2023

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 103

Management Advertising Data Lake Sales 103

Alation

MAY 16, 2023

Sources can include analytics data regarding user behavior, transactional data from ecommerce websites, and third-party data from other organizations. It’s worth noting that a data pipeline may have more than one data source. Ingestion tools are connected to various data sources.

Data Lake 40

Data Lake Data Governance Data Warehouse Data Processing 40

Cloudera

DECEMBER 8, 2020

Federated Learning is a paradigm in which machine learning models are trained on decentralized data. Instead of collecting data on a single server or data lake, it remains in place — on smartphones, industrial sensing equipment, and other edge devices — and models are trained on-device.

Machine Learning 85

Machine Learning Data Lake Reporting Modeling 85

CIO Business Intelligence

JUNE 9, 2022

All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. Marketing-focused or not, DMPs excel at negotiating with a wide array of databases, data lakes, or data warehouses, ingesting their streams of data and then cleaning, sorting, and unifying the information therein.

Management 144

Management Advertising Data Lake Sales 144

CIO Business Intelligence

MAY 26, 2022

MLOps covers the full gamut from data collection, verification, and analysis, all the way to managing machine resources and tracking model performance. Data lakes work well for companies doing a lot of analytics at high frequencies who are looking for low-cost storage, for example.

Machine Learning 145

Machine Learning Modeling Data-driven Enterprise 145