CIO Business Intelligence

OCTOBER 25, 2022

Finally, the problem was shared by the enterprise at large. That insight told them what data they would need, which in turn allowed ChampionX’s IT and Commercial Digital teams to discern who and what they needed to capture it. They needed IoT sensors, for example, to extract relevant data from the sites.

Data Strategy 145

Data Strategy Strategy Data Lake Data-driven 145

AWS Big Data

JANUARY 8, 2024

In the subsequent post in our series, we will explore the architectural patterns in building streaming pipelines for real-time BI dashboards, contact center agent, ledger data, personalized real-time recommendation, log analytics, IoT data, Change Data Capture, and real-time marketing data.

Analytics 111

Analytics IoT Data-driven Snapshot 111

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.

Analytics 69

Analytics Data Warehouse Data Lake Metadata 69

CIO Business Intelligence

JULY 12, 2023

However, some things are common to virtually all types of manufacturing: expensive equipment and trained human operators are always required, and both the machinery and the people need to be deployed in an optimal manner to keep costs down. We created a data lake, so we have access to all that data in a very efficient way,” says Papermaster.

Manufacturing 98

Manufacturing Cost-Benefit Data Lake Optimization 98

AWS Big Data

FEBRUARY 6, 2023

Additionally, a TCO calculator generates the TCO estimation of an optimized EMR cluster for facilitating the migration. Have an AWS account with permission on AWS Lambda , QuickSight (Enterprise edition), and AWS CloudFormation. For the compute-heavy workloads such as MapReduce or Hive-on-MR jobs, use CPU-optimized instances.

Dashboards 73

Dashboards Optimization Data Lake Cost-Benefit 73

Cloudera

MAY 12, 2021

Use cases could include but are not limited to: predictive maintenance, log data pipeline optimization, connected vehicles, industrial IoT, fraud detection, patient monitoring, network monitoring, and more. DATA FOR ENTERPRISE AI. Nominations for the 2021 Cloudera Data Impact Awards are open from now until July 23.

Digital Transformation 68

Digital Transformation Machine Learning Optimization Data Lake 68

AWS Big Data

NOVEMBER 14, 2023

Ten years ago, we launched Amazon Kinesis Data Streams , the first cloud-native serverless streaming data service, to serve as the backbone for companies, to move data across system boundaries, breaking data silos. Enhanced Fan-out offers dedicated read throughput and low latency for each data consumer.

IoT 56

IoT Data-driven Data Lake Data Strategy 56

AWS Big Data

FEBRUARY 6, 2023

When migrating Hadoop workloads to Amazon EMR , it’s often difficult to identify the optimal cluster configuration without analyzing existing workloads by hand. It enables compute such as EMR instances and storage such as Amazon Simple Storage Service (Amazon S3) data lakes to scale. For more information, see the GitHub repo.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

AWS Big Data

FEBRUARY 21, 2023

Because data is closer to the source and stored in raw format, it has to be transformed before it can be used for reporting and other application purposes. This is one of the biggest hurdles with the data vault approach. What is a dimensional data model? It optimizes the database for faster data retrieval.

Data Warehouse 63

Data Warehouse Data Lake Cost-Benefit Modeling 63

Corinium

APRIL 25, 2019

And it’s become a hyper-competitive business, so enhancing customer service through data is critical for maintaining customer loyalty. And more recently, we have also seen innovation with IOT (Internet Of Things). Why should Chief Data & Analytics Officers care about data security? That’s the reward.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

Cloudera

FEBRUARY 19, 2018

But when companies are looking towards new technologies such as data lakes, machine learning or predictive analytics, SAP alone is just not enough. To keep up with tech trends, businesses have to face the challenges of integrating SAP with non-SAP technologies and embark on a crusade against data silos.

Data Lake 46

Data Lake Finance Data Governance Big Data 46

FineReport

APRIL 11, 2023

Additionally, they provide tabs, pull-down menus, and other navigation features to assist in accessing data. Data Visualizations : Dashboards are configured with a variety of data visualizations such as line and bar charts, bubble charts, heat maps, and scatter plots to show different performance metrics and statistics.

Dashboards 40

Dashboards Business Intelligence Cost-Benefit Metrics 40

Cloudera

DECEMBER 19, 2018

Business intelligence (BI), an umbrella term coined in 1989 by Howard Dresner, Chief Research Officer at Dresner Advisory Services, refers to the ability of end-users to access and analyze enterprise data. The most common big data use case is data warehouse optimization.

Data Warehouse 52

Data Warehouse Analytics Big Data Data Architecture 52

CIO Business Intelligence

JUNE 29, 2022

If you can’t make sense of your business data, you’re effectively flying blind. Insights hidden in your data are essential for optimizing business operations, finetuning your customer experience, and developing new products — or new lines of business, like predictive maintenance. Azure Data Lake Analytics.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

Cloudera

JANUARY 30, 2023

And this doesn’t even touch on the data generated by citizen services interfaces, machine or device-generated data such as video feeds, sensors, and communications data. Some examples include employee records, internal and external communications, photo, video, and audio files, IoT sensor data, and streamed data.

IoT 81

IoT Data Architecture Data Lake Machine Learning 81

Cloudera

JUNE 9, 2022

In the first blog of the Universal Data Distribution blog series , we discussed the emerging need within enterprise organizations to take control of their data flows. controlling distribution while also allowing the freedom and flexibility to deliver the data to different services is more critical than ever. .

Data Collection 92

Data Collection IoT Data Lake Unstructured Data 92

IBM Big Data Hub

JANUARY 18, 2023

Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

Cloudera

MAY 9, 2023

The company also provides a variety of solutions for enterprises, including data centers, cloud, security, global, artificial intelligence (AI), IoT, and digital marketing services. Supporting Data Access to Achieve Data-Driven Innovation Due to the spread of COVID-19, demand for digital services has increased at SoftBank.

Data Lake 89

Data Lake IoT Data Governance Data Strategy 89

CIO Business Intelligence

APRIL 18, 2023

By: Gayle Levin, Senior Product Marketing Manager for Wireless at Aruba, A Hewlett Packard Enterprise Company. Cloud-based network management increases agility and allows resource-constrained IT departments to focus on optimizing the network, not deploying, managing, or upgrading the network management system.

IoT 52

IoT Internet of Things Data Lake Optimization 52

Cloudera

SEPTEMBER 6, 2022

Data has continued to grow both in scale and in importance through this period, and today telecommunications companies are increasingly seeing data architecture as an independent organizational challenge, not merely an item on an IT checklist. Previously, there were three types of data structures in telco: .

Data Architecture 83

Data Architecture Cost-Benefit Digital Transformation Business Driver 83

Alation

APRIL 14, 2022

Moving data to the cloud can bring immense operational benefits. However, the sheer volume and complexity of today’s enterprise data can cause downstream headaches for data users. Semantics, context, and how data is tracked and used mean even more as you stretch to reach post-migration goals.

Metadata 59

Metadata Data Governance Modeling Data-driven 59

Sisense

MAY 11, 2021

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021!

Modeling 84

Modeling Big Data IoT Data Warehouse 84

erwin

DECEMBER 13, 2018

Data policies as a consumer buying criteria : The threat of “data trauma” will continue to drive visibility for enterprise data in the C-suite. How they respond will be the key to their long-term success in transforming data into a true enterprise asset. Data is no longer just an IT issue.

Data Governance 91

Data Governance IoT Internet of Things Data-driven 91

Cloudera

OCTOBER 7, 2021

Those decentralization efforts appeared under different monikers through time, e.g., data marts versus data warehousing implementations (a popular architectural debate in the era of structured data) then enterprise-wide data lakes versus smaller, typically BU-Specific, “data ponds”.

Metadata 123

Metadata Cost-Benefit Enterprise Interactive 123

CIO Business Intelligence

DECEMBER 6, 2023

Laying the data foundation The four pillars of DS Smith’s digital plan revolved around the management and optimization of data generated by industrial machines, energy providers, its supply chain, and customer experience. Having that data in the cloud and piping it into our data pipelines is a much more effective way to do that.”

Manufacturing 94

Manufacturing Data Lake Digital Transformation Machine Learning 94

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. 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