IBM Big Data Hub

JANUARY 12, 2024

The integration of artificial intelligence (AI) has ushered in a new era of technological progress, offering a spectrum of benefits across industries. However, as AI services find a home in cloud platforms, the issue of data confidentiality takes center stage.

Data-driven 104

Data-driven Interactive Data Processing Technology 104

AWS Big Data

JANUARY 8, 2024

We’re living in the age of real-time data and insights, driven by low-latency data streaming applications. The volume of time-sensitive data produced is increasing rapidly, with different formats of data being introduced across new businesses and customer use cases.

Analytics 112

Analytics IoT Data-driven Snapshot 112

CIO Business Intelligence

OCTOBER 13, 2023

In the next six to 12 months, some of the most popular anticipated uses for gen AI include content creation (42%), data analytics (53%), software development (41%), business insight (51%), internal customer support (45%), product development (40%), security (42%), and process automation (51%).

Deep Learning 143

Deep Learning Machine Learning Modeling Software 143

Cloudera

SEPTEMBER 21, 2021

Many customers looking at modernizing their pipeline orchestration have turned to Apache Airflow, a flexible and scalable workflow manager for data engineers. But now it has become very simple and secure with our release of the Cloudera Airflow provider , which gives users the best of Airflow and CDP data services.

Data Processing 93

Data Processing Testing Management Machine Learning 93

CIO Business Intelligence

FEBRUARY 14, 2023

By George Trujillo, Principal Data Strategist, DataStax Increased operational efficiencies at airports. To succeed with real-time AI, data ecosystems need to excel at handling fast-moving streams of events, operational data, and machine learning models to leverage insights and automate decision-making.

Data Strategy 116

Data Strategy Strategy Machine Learning Data-driven 116

Cloudera

JUNE 28, 2022

In a previous blog of this series, Turning Streams Into Data Products , we talked about the increased need for reducing the latency between data generation/ingestion and producing analytical results and insights from this data. containing data that may have to be used to enrich the streaming data. The use case.

Dashboards 80

Dashboards Machine Learning Statistics KPI 80

IBM Big Data Hub

FEBRUARY 14, 2024

The easy answer is mostly manual labor, although the day might come when much of what is now manual labor will be accomplished by robotic devices controlled by AI. Not only will this help scale the AOT tech across markets, but it will also help tackle integrations including additional languages, dialects and menu variations.

Cost-Benefit 88

Cost-Benefit Insurance Unstructured Data Machine Learning 88

AWS Big Data

NOVEMBER 26, 2023

Amazon EMR is pleased to announce integration with Amazon Simple Storage Service ( Amazon S3 ) Access Grants that simplifies Amazon S3 permission management and allows you to enforce granular access at scale. First, we’ll run a batch job on EMR on Amazon EC2 to import CSV data and convert to Parquet.

Interactive 101

Interactive Dashboards Management Cost-Benefit 101

IBM Big Data Hub

AUGUST 8, 2023

Examples of transportation systems include roadways, public transit systems, airports, train stations, bus stations, ferry terminals, pipelines and warehouses. By integrating EHS monitoring into their asset maintenance programs, they can self-police, monitoring their emissions and ensuring they stay in compliance.

Internet of Things 71

Internet of Things IoT Cost-Benefit Optimization 71

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

Birst BI

NOVEMBER 20, 2018

When you hear about Data Science, Big Data, Analytics, Artificial Intelligence, Machine Learning, or Deep Learning, you may end up feeling a bit confused about what these terms mean. The simplest answer is that these terms refer to some of the many analytic methods available to Data Scientists. What are overlaps and differences?

Statistics 84

Statistics Machine Learning Deep Learning Optimization 84

DataKitchen

APRIL 13, 2021

This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Companies that implement DataOps find that they are able to reduce cycle times from weeks (or months) to days, virtually eliminate data errors, increase collaboration, and dramatically improve productivity.

Testing 307

Testing Machine Learning Consulting Data Quality 307

O'Reilly on Data

APRIL 9, 2019

A few months ago, I wrote about the differences between data engineers and data scientists. An interesting thing happened: the data scientists started pushing back, arguing that they are, in fact, as skilled as data engineers at data engineering. Otherwise, this leads to failure with big data projects.

Data Science 278

Data Science Big Data Management ROI 278

IBM Big Data Hub

NOVEMBER 13, 2023

But Docker lacked an automated “orchestration” tool, which made it time-consuming and complex for data science teams to scale applications. Kubernetes can also run on bare metal servers and virtual machines (VMs) in private cloud, hybrid cloud and edge settings, provided the host OS is a version of Linux or Windows.

Machine Learning 117

Machine Learning Data-driven Software Testing 117

CIO Business Intelligence

FEBRUARY 28, 2024

However, getting into the more difficult types of implementations — the fine-tuned models, vector databases to provide context and up-to-date information to the AI systems, and APIs to integrate gen AI into workflows — is where problems might crop up. They need stability. in December. That’s fine, but language models are great for language.

IT 132

IT Consulting Modeling Enterprise 132

Cloudera

SEPTEMBER 17, 2020

For enterprise organizations, managing and operationalizing increasingly complex data across the business has presented a significant challenge for staying competitive in analytic and data science driven markets. CDP data lifecycle integration and SDX security and governance.

Visualization 101

Visualization Metrics Statistics Optimization 101

AWS Big Data

JUNE 29, 2023

Amazon Kinesis Data Analytics makes it easy to transform and analyze streaming data in real time. In this post, we discuss why AWS recommends moving from Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics for Apache Flink to take advantage of Apache Flink’s advanced streaming capabilities.

Data Analytics 74

Data Analytics Analytics IoT Data Lake 74

IBM Big Data Hub

OCTOBER 12, 2023

Connecting AI models to a myriad of data sources across cloud and on-premises environments AI models rely on vast amounts of data for training. Once trained and deployed, models also need reliable access to historical and real-time data to generate content, make recommendations, detect errors, send proactive alerts, etc.

Cost-Benefit 83

Cost-Benefit Metadata Data Governance Modeling 83

Ontotext

JANUARY 20, 2022

They focus on business-specific information needs and how to properly source the needed data rather than analyze preexisting application models. Building a single data graph across the three services. Analyzing Unstructured Data with GraphDB 9.8. To be able to interact with such systems, we need the proper tooling for it.

Enterprise 52

Enterprise Unstructured Data Modeling Visualization 52

Alation

JANUARY 25, 2022

Data fabric is now on the minds of most data management leaders. In our previous blog, Data Mesh vs. Data Fabric: A Love Story , we defined data fabric and outlined its uses and motivations. The data catalog is a foundational layer of the data fabric.

Metadata 52

Metadata IT Metrics Data-driven 52

AWS Big Data

NOVEMBER 1, 2023

Amazon Redshift is a fully managed, petabyte scale cloud data warehouse that enables you to analyze large datasets using standard SQL. Data warehouse workloads are increasingly being used with mission-critical analytics applications that require the highest levels of resilience and availability.

Data Warehouse 94

Data Warehouse Snapshot Testing Management 94

CDW Research Hub

SEPTEMBER 30, 2019

Cutco enables their sales teams to perform direct sales using applications hosted in Cutco’s traditional data centers. VPN connectivity to Cutco’s primary data center and a colocation facility. Cutco Cutlery Corp. is a privately held organization headquartered in Olean, NY. The Challenge.

Sales 40

Sales Software Cost-Benefit Testing 40

CIO Business Intelligence

FEBRUARY 3, 2023

Using RPA tools, a company can configure software, or a “robot,” to capture and interpret applications for processing a transaction, manipulating data, triggering responses, and communicating with other digital systems. RPA benefits RPA is also a relatively simple way to integrate AI algorithms into old applications.

Data-driven 145

Data-driven Interactive Enterprise Statistics 145

Cloudera

JUNE 16, 2022

The ability to perform analytics on data as it is created and collected (a.k.a. real-time data streams) and generate immediate insights for faster decision making provides a competitive edge for organizations. . CSP was recently recognized as a leader in the 2022 GigaOm Radar for Streaming Data Platforms report.

Data Lake 83

Data Lake Manufacturing Metadata Dashboards 83

Cloudera

OCTOBER 11, 2021

Modak, a leading provider of modern data engineering solutions, is now a certified solution partner with Cloudera. Customers can now seamlessly automate migration to Cloudera’s Hybrid Data Platform — Cloudera Data Platform (CDP) to dynamically auto-scale cloud services with Cloudera Data Engineering (CDE) integration with Modak Nabu.

Data Lake 89

Data Lake Cost-Benefit Data-driven Dashboards 89

O'Reilly on Data

JANUARY 25, 2021

In this report, we look at the data generated by the O’Reilly online learning platform to discern trends in the technology industry—trends technology leaders need to follow. Sometimes they’re only apparent if you look carefully at the data; sometimes it’s just a matter of keeping your ear to the ground. But what are “trends”?

Machine Learning 363

Machine Learning Software Testing Technology 363

IBM Big Data Hub

FEBRUARY 9, 2024

2024 thus stands to be a pivotal year for the future of AI, as researchers and enterprises seek to establish how this evolutionary leap in technology can be most practically integrated into our everyday lives. The evolution of generative AI has mirrored that of computers, albeit on a dramatically accelerated timeline.

Cost-Benefit 105

Cost-Benefit Modeling Data-driven Enterprise 105