IBM Big Data Hub

DECEMBER 5, 2023

Generative AI excels at handling diverse data sources such as emails, images, videos, audio files and social media content. This unstructured data forms the backbone for creating models and the ongoing training of generative AI, so it can stay effective over time.

Unstructured Data 92

Unstructured Data Cost-Benefit Experimentation Machine Learning 92

Cloudera

JANUARY 5, 2021

Website Operations —Analyze website operations to improve efficiencies in order fulfillment service levels, optimize delivery options offered. Consolidated Inventory & Sales Data — Build an enterprise view of sales and inventory across all channels. Additional retail content can be found at our retail resource kit .

Forecasting 90

Forecasting Cost-Benefit Sales Unstructured Data 90

IBM Big Data Hub

AUGUST 22, 2023

It uses real-world data (both real time and historical) combined with engineering, simulation or machine learning (ML) models to enhance operations and support human decision-making. appeared first on IBM Blog.

Unstructured Data 77

Unstructured Data Consulting Visualization IoT 77

datapine

NOVEMBER 19, 2019

In this day and age, we’re all constantly hearing the terms “big data”, “data scientist”, and “in-memory analytics” being thrown around. Almost all the major software companies are continuously making use of the leading Business Intelligence (BI) and Data discovery tools available in the market to take their brand forward.

Business Intelligence 146

Business Intelligence Knowledge Discovery Dashboards Unstructured Data 146

IBM Big Data Hub

MAY 14, 2024

A generative AI agent or assistant can ingest and summarize structured and unstructured data from internal and external sources, parse through it and generate insights and patterns for financial information that can drive business value and potentially identify untapped revenue streams.

Finance 71

Finance Cost-Benefit Reporting Forecasting 71

IBM Big Data Hub

OCTOBER 30, 2023

IBM, a pioneer in data analytics and AI, offers watsonx.data, among other technologies, that makes possible to seamlessly access and ingest massive sets of structured and unstructured data. The retailer uses these insights to optimize inventory levels, reduce costs and enhance efficiency.

Insurance 81

Insurance Data Warehouse Data-driven Unstructured Data 81

IBM Big Data Hub

FEBRUARY 14, 2024

By infusing AI into IT operations , companies can harness the considerable power of NLP, big data, and ML models to automate and streamline operational workflows, and monitor event correlation and causality determination. Generative AI can speed and optimize product design by helping companies create multiple design options.

Cost-Benefit 85

Cost-Benefit Insurance Unstructured Data Machine Learning 85

AWS Big Data

OCTOBER 20, 2023

We’ve seen a demand to design applications that enable data to be portable across cloud environments and give you the ability to derive insights from one or more data sources. With these connectors, you can bring the data from Azure Blob Storage and Azure Data Lake Storage separately to Amazon S3. Learn more in README.

Data Lake 87

Data Lake Big Data Consulting Data Warehouse 87

AWS Big Data

SEPTEMBER 8, 2023

In this blog post, we discuss the impact of Amazon Elastic Block Store (Amazon EBS) volume IOPS and throughput limits on Amazon OpenSearch Service domain and how to prevent/mitigate throughput throttling situation. Maximum allowed IOPS or the throughput value of the Amazon EBS volume used by the data node.

Management 94

Management Metrics Measurement Unstructured Data 94

IBM Big Data Hub

JANUARY 5, 2023

The first generation of data architectures represented by enterprise data warehouse and business intelligence platforms were characterized by thousands of ETL jobs, tables, and reports that only a small group of specialized data engineers understood, resulting in an under-realized positive impact on the business.

Data Quality 52

Data Quality Data Architecture Strategy Data Lake 52

AWS Big Data

JULY 19, 2023

We’ve seen that there is a demand to design applications that enable data to be portable across cloud environments and give you the ability to derive insights from one or more data sources. With this connector, you can bring the data from Google Cloud Storage to Amazon S3.

Big Data 85

Big Data Software Consulting Unstructured Data 85

Cloudera

OCTOBER 28, 2021

The German underwriters analyzed historical data such as weather, location, breed, type of crop, and a farmer’s experience to assess risk, underwrite and set price exposures. In this way, the Commercial Lines segment of insurance has really been a user of big data since its inception. Another example is fleet management.

Insurance 94

Insurance Risk Unstructured Data Data-driven 94

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? This post will dive deeper into the nuances of each field.

Machine Learning 56

Machine Learning Data Science Statistics Deep Learning 56

AWS Big Data

JANUARY 8, 2024

Therefore, it is critical for organizations to embrace a low-latency, scalable, and reliable data streaming infrastructure to deliver real-time business applications and better customer experiences. Stream ingestion – The stream ingestion layer is responsible for ingesting data into the stream storage layer.

Analytics 115

Analytics IoT Data-driven Snapshot 115

Cloudera

SEPTEMBER 10, 2018

Among the many reasons that a majority of large enterprises have adopted Cloudera Data Warehouse as their modern analytic platform of choice is the incredible ecosystem of partners that have emerged over recent years. Informatica’s Big Data Manager and Qlik’s acquisition of Podium Data are just 2 examples.

Data Warehouse 43

Data Warehouse Unstructured Data Internet of Things Enterprise 43

datapine

JUNE 5, 2019

Without the existence of dashboards and dashboard reporting practices, businesses would need to sift through colossal stacks of unstructured data, which is both inefficient and time-consuming. With such dashboards, users can also customize settings, functionality, and KPIs to optimize their dashboards to suit their specific needs.

Dashboards 316

Dashboards KPI Sales Visualization 316

IBM Big Data Hub

FEBRUARY 2, 2023

Misconception 3: All data warehouse migrations are the same, irrespective of vendors While migrating to the cloud, CTOs often feel the need to revamp and “modernize” their entire technology stack – including moving to a new cloud data warehouse vendor.

Data Warehouse 56

Data Warehouse Cost-Benefit Unstructured Data Data Architecture 56

Sisense

OCTOBER 6, 2020

Digging into quantitative data Why is quantitative data important What are the problems with quantitative data Exploring qualitative data Qualitative data benefits Getting the most from qualitative data Better together. The result, as Sisense CEO Amir Orad wrote , is that every company is now a data company.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

AWS Big Data

MARCH 2, 2023

How Apache Iceberg addresses what customers want in modern data lakes More and more customers are building data lakes, with structured and unstructured data, to support many users, applications, and analytics tools. We use iceberg-blog-cluster. all_reviews ): data and metadata. Choose Next.

Data Lake 120

Data Lake Data Processing Metadata Snapshot 120

IBM Big Data Hub

DECEMBER 16, 2022

Meanwhile, the company’s IT teams could optimize their time by focusing on other important workloads. Comprehensive search and access to relevant data. Because Alex can use a data catalog to search all data assets across the company, she has access to the most relevant and up-to-date information.

Metadata 52

Metadata Data Quality Data-driven Data Governance 52

IBM Big Data Hub

AUGUST 28, 2023

Named entity recognition (NER): NER extracts relevant information from unstructured data by identifying and classifying named entities (like person names, organizations, locations and dates) within the text. A targeted approach will optimize the user experience and enhance an organization’s ROI.

Data mining 56

Data mining Machine Learning Deep Learning Marketing 56

IBM Big Data Hub

DECEMBER 4, 2023

IBM® watsonx ™ AI and data platform, along with its suite of AI assistants, is designed to help scale and accelerate the impact of AI using trusted data throughout the business. The most common insurance use cases include optimizing processes that require processing large documents and large blocks of text or images.

Insurance 54

Insurance Digital Transformation Risk Management Interactive 54

Cloudera

SEPTEMBER 7, 2018

Moreover, this approach struggles to deal with the large volume and variety of data that must be analyzed and often correlated. Analyzing unstructured data sets such as text, audio and images are challenging, especially while determining illegal intent in communications. The blog is the joint property of Accenture and Cloudera.

Machine Learning 49

Machine Learning Risk Unstructured Data Cost-Benefit 49

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 Big Data Ecosystem.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

Jedox

FEBRUARY 13, 2019

As organizations strive to implement an analytics culture for data-driven decision making, AI can be an important component in that process. These new tools will support ad-hoc reporting that can leverage unstructured data. appeared first on Jedox BI Blog. The post Is AI Enhancing or Disrupting FP&A as We Know It?

IT 54

IT Finance Cost-Benefit Unstructured Data 54

Sisense

MAY 28, 2020

In the Clouds is where we explore the ways cloud-native architecture, cloud data storage, and cloud analytics are changing key industries and business practices, with anecdotes from experts, how-to’s, and more to help your company excel in the cloud era. The world of data is constantly changing and speeding up every day. “Not

Internet of Things 83

Internet of Things Metadata Data-driven Unstructured Data 83

datapine

NOVEMBER 19, 2019

In this day and age, we’re all constantly hearing the terms “big data”, “data scientist”, and “in-memory analytics” being thrown around. Almost all the major software companies are continuously making use of the leading Business Intelligence (BI) and Data Discovery tools available in the market to take their brand forward.

Business Intelligence 20

Business Intelligence Knowledge Discovery Unstructured Data Software 20

Rita Sallam

JULY 22, 2016

By contrast, traditional BI platforms are designed to support modular development of IT-produced analytic content, specialized tools and skills, and significant upfront data modeling, coupled with a predefined metadata layer, is required to access their analytic capabilities. Some Additional Questions and Answers. Enjoy your summer!!

Analytics 40

Analytics Business Intelligence Metadata Statistics 40

DataKitchen

APRIL 13, 2021

Read the complete blog below for a more detailed description of the vendors and their capabilities. This is not surprising given that DataOps enables enterprise data teams to generate significant business value from their data. Genie — Distributed big data orchestration service by Netflix. Data breaks.

Testing 300

Testing Machine Learning Consulting Data Quality 300

Cloudera

SEPTEMBER 15, 2022

Structured data (such as name, date, ID, and so on) will be stored in regular SQL databases like Hive or Impala databases. There are also newer AI/ML applications that need data storage, optimized for unstructured data using developer friendly paradigms like Python Boto API. Diversity of workloads.

Metadata 86

Metadata Big Data Optimization Unstructured Data 86

Sisense

MAY 4, 2020

Data’s more influential than ever, but just how much data is there? In The Wide World of Data , we dig into astonishing facts and trends about the size and growth of the datasphere, how data is being used, and how it truly makes up the entire world around us. Information about the size and growth of data is abundant.

Big Data 78

Big Data Data-driven Snapshot Unstructured Data 78

IBM Big Data Hub

JULY 6, 2023

This blog post will clarify some of the ambiguity. AI uses predictions and automation to optimize and solve complex tasks that humans have historically done, such as facial and speech recognition, decision making and translation. Machine learning is a subset of artificial intelligence that allows for optimization.

Deep Learning 59

Deep Learning Machine Learning Unstructured Data Modeling 59

IBM Big Data Hub

JANUARY 17, 2023

Technical Metadata storage/service: This component is required to understand what data is available in the storage layer. The query engine needs the metadata for the unstructured data and tables to understand where the data is located, what it looks like, and how to read it. appeared first on Journey to AI Blog.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

Cloudera

JULY 29, 2022

Corporations are generating unprecedented volumes of data, especially in industries such as telecom and financial services industries (FSI). However, not all these organizations will be successful in using data to drive business value and increase profits. Is yours among the organizations hoping to cash in big with a big data solution?

Data Architecture 84

Data Architecture Data Strategy Risk Management Strategy 84

IBM Big Data Hub

JANUARY 10, 2024

Data is often divided into three categories: training data (helps the model learn), validation data (tunes the model) and test data (assesses the model’s performance). For optimal performance, AI models should receive data from a diverse datasets (e.g.,

Unstructured Data 79

Unstructured Data Deep Learning Cost-Benefit Modeling 79

AWS Big Data

JULY 20, 2023

The Orca Platform is powered by a state-of-the-art anomaly detection system that uses cutting-edge ML algorithms and big data capabilities to detect potential security threats and alert customers in real time, ensuring maximum security for their cloud environment. Why did Orca choose Apache Iceberg?

Data Lake 89

Data Lake Analytics Snapshot Optimization 89

Alation

MARCH 21, 2023

To fully realize data’s value, organizations in the travel industry need to dismantle data silos so that they can securely and efficiently leverage analytics across their organizations. What is big data in the travel and tourism industry? What are common data challenges for the travel industry?

Data Analytics 52

Data Analytics Analytics Data-driven Big Data 52