AWS Big Data

MARCH 25, 2024

A RAG-based generative AI application can only produce generic responses based on its training data and the relevant documents in the knowledge base. For example, Amazon DynamoDB provides a feature for streaming CDC data to Amazon DynamoDB Streams or Kinesis Data Streams.

Data Lake 89

Data Lake Unstructured Data Management Modeling 89

datapine

JUNE 5, 2019

Data dashboards provide a centralized, interactive means of monitoring, measuring, analyzing, and extracting a wealth of business insights from relevant datasets in several key areas while displaying aggregated information in a way that is both intuitive and visual. Data being spread out amongst many databases.

Dashboards 316

Dashboards KPI Sales Visualization 316

datapine

NOVEMBER 19, 2019

Discovery and documentation serve as key features in collaborative BI. This kind of analysis leads to feedback that can aid in improving the decision-making process, letting companies document the best practices and monitor the data that’s the most useful in this scenario. However, collaborative BI helps in changing that.

Business Intelligence 146

Business Intelligence Knowledge Discovery Dashboards Unstructured Data 146

erwin

JANUARY 17, 2020

What is Data Modeling? Data modeling is a process that enables organizations to discover, design, visualize, standardize and deploy high-quality data assets through an intuitive, graphical interface. Data models provide visualization, create additional metadata and standardize data design across the enterprise.

Data-driven 138

Data-driven Modeling Metadata Data Governance 138

AWS Big Data

OCTOBER 25, 2023

Unstructured data is information that doesn’t conform to a predefined schema or isn’t organized according to a preset data model. Unstructured information may have a little or a lot of structure but in ways that are unexpected or inconsistent. Text, images, audio, and videos are common examples of unstructured data.

Unstructured Data 118

Unstructured Data Metadata Management Analytics 118

IBM Big Data Hub

AUGUST 28, 2023

These are two common methods for text representation: Bag-of-words (BoW): BoW represents text as a collection of unique words in a text document. Term frequency-inverse document frequency (TF-IDF): TF-IDF calculates the importance of each word in a document based on its frequency or rarity across the entire dataset.

Data mining 53

Data mining Machine Learning Deep Learning Marketing 53

Cloudera

SEPTEMBER 1, 2020

DDE also makes it much easier for application developers or data workers to self-service and get started with building insight applications or exploration services based on text or other unstructured data (i.e. data best served through Apache Solr). Stores source documents. What does DDE entail?

Snapshot 71

Snapshot Unstructured Data Dashboards Interactive 71

bridgei2i

NOVEMBER 25, 2020

From underwriting processes that typically involved manual effort (in gathering data from documents), enterprises have now shifted to automation with a digital core that can make it easier to analyze several types of data formats—textual, visual, sensor-based and electronic.

Insurance 52

Insurance Sales Strategy Digital Transformation 52

AWS Big Data

MARCH 7, 2024

You can take all your data from various silos, aggregate that data in your data lake, and perform analytics and machine learning (ML) directly on top of that data. You can also store other data in purpose-built data stores to analyze and get fast insights from both structured and unstructured data.

Data Lake 112

Data Lake Analytics Dashboards Metrics 112

FineReport

APRIL 26, 2023

Having visually appealing graphics can also increase user adoption. Advanced analytics capabilities : The tool should be able to analyze data and identify patterns, as well as forecast future events with complex forecasting algorithms, going beyond simple mathematical calculations. It supports master-slave replication for data backup.

Big Data 52

Big Data Data Analytics Analytics Cost-Benefit 52

Alation

JUNE 2, 2022

Data management is not yet a solved problem, but modern data management is leagues ahead of prior approaches. These include tracking, documenting, monitoring, versioning, and controlling access to AI/ML models. A data catalog is a central hub for XAI and understanding data and related models. Other Technologies.

Modeling 52

Modeling Data Governance Statistics Unstructured Data 52

CIO Business Intelligence

AUGUST 17, 2023

The impact could really be that profound since we have a tool that can be applied to multiple use cases, from writing and designing products, to visualizations, checking code, and so forth.” It’s made my life easier because it allows me to write documents and make them richer, but if you rely on this beast it can bite you.

Risk 87

Risk Cost-Benefit Strategy Experimentation 87

bridgei2i

OCTOBER 7, 2020

To catch up, underwriting which typically involved manual involvement in garnering data from documents has to change radically. Application validation – Automated process to check the required documents availability. (if The more data an underwriter has at his disposal, the more accurately he will be able to assess risk.

Insurance 52

Insurance Sales Strategy Digital Transformation 52

Octopai

JUNE 24, 2019

Additionally, features that manage data relationships through hierarchies make this process much easier. Document classification and lifecycle management will help you deal with oversight of unstructured data. This maintains a high priority in your data governance strategy.

Data Governance 42

Data Governance Metadata Unstructured Data Software 42

datapine

NOVEMBER 19, 2019

Discovery and documentation serve as key features in collaborative BI. This kind of analysis leads to feedback that can aid in improving the decision-making process, letting companies document the best practices and monitor the data that’s the most useful in this scenario. However, collaborative BI helps in changing that.

Business Intelligence 20

Business Intelligence Knowledge Discovery Unstructured Data Software 20

Smart Data Collective

SEPTEMBER 26, 2021

Data mining and knowledge go hand in hand, providing insightful information to create applications that can make predictions, identify patterns, and, last but not least, facilitate decision-making. Working with massive structured and unstructured data sets can turn out to be complicated. A document is susceptible to change.

Metadata 98

Metadata Visualization Unstructured Data Data mining 98

Cloudera

NOVEMBER 25, 2020

For example, it includes patient samples (blood, blood pressure, temperature, and more), patient information (age, gender, where they have lived, family situation, and other details), and treatment history, most of which is currently found only in paper documents. The Vision of a Discovery Data Warehouse.

Data Warehouse 59

Data Warehouse Unstructured Data Analytics Visualization 59

Ontotext

JANUARY 20, 2022

Analyzing Unstructured Data with GraphDB 9.8. The first webinar explores what to do when you already have RDF data and want to access it in flexible ways. He focuses on the graph database and how to call external TA services, which are doing the heavy lifting of analyzing the unstructured data and returning textual annotations.

Enterprise 52

Enterprise Unstructured Data Modeling Visualization 52

IBM Big Data Hub

SEPTEMBER 13, 2023

To drive personalized actions, insights and visibility, large volumes of data (ERP, WMS, RFID and visual analytics) need to be ingested, normalized and analyzed at high speeds. They get contextual information as well as factual data (PDFs, visual images, RFID tags information).

Visualization 67

Visualization Unstructured Data Interactive Technology 67

IBM Big Data Hub

SEPTEMBER 19, 2022

One way to achieve real-time analytics is with a combination of a time-series database (InfluxDB or TimescaleDB) or a NoSQL database (MongoDB) + a data warehouse + a BI tool: This architecture raises a question: Why would one use an operational database, and still need a data warehouse ? But wait, it gets better….

IoT 52

IoT Analytics Data Warehouse Manufacturing 52

Ontotext

FEBRUARY 26, 2024

Further, RED’s underlying model can be visually extended and customized to complex extraction and classification tasks. RED’s focus on news content serves a pivotal function: identifying, extracting, and structuring data on events, parties involved, and subsequent impacts. Here’s how our tool makes it work.

Data-driven 59

Data-driven Risk Modeling Risk Management 59

Sisense

AUGUST 21, 2020

One result is that systems become much more intuitive: Users can take advantage of the “Simply Ask” feature to check “what are my sales next two months” and receive chatbot messages with projected visualizations and suggestions for further exploration routes. My take: The world is wider than the traditional BI tabular data.

Analytics 112

Analytics Machine Learning Dashboards Visualization 112

IBM Big Data Hub

MAY 17, 2023

The services are activated through access management for data collection, analysis and event monitoring in existing drones which are managed by clients and businesses. The flexibility of DaaS in offering a multiplicity of data collection services for different industry use cases makes it unique.

Data Collection 77

Data Collection Visualization Data-driven Unstructured Data 77

erwin

JUNE 27, 2019

Additional challenges, such as increasing regulatory pressures – from the General Data Protection Regulation (GDPR) to the Health Insurance Privacy and Portability Act (HIPPA) – and growing stores of unstructured data also underscore the increasing importance of a data modeling tool.

Measurement 81

Measurement Modeling Unstructured Data Metadata 81

Cloudera

AUGUST 16, 2021

Apache Nifi is a powerful tool to build data movement pipelines using a visual flow designer. Hundreds of built-in processors make it easy to connect to any application and transform data structures or data formats as needed.

Dashboards 122

Dashboards Metrics KPI Data-driven 122

Sisense

JULY 22, 2020

They hold structured data from relational databases (rows and columns), semi-structured data ( CSV , logs, XML , JSON ), unstructured data (emails, documents, PDFs), and binary data (images, audio , video). Sisense provides instant access to your cloud data warehouses. Building dashboards and widgets.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

datapine

FEBRUARY 22, 2022

They can govern the implementation with a documented business case and be responsible for changes in scope. On the flip side, document everything that isn’t working. What data analysis questions are you unable to currently answer? The goal is to boost the ROI of your department – and any other – that are relying on this data.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Rocket-Powered Data Science

MARCH 20, 2023

Data collections are the ones and zeroes that encode the actionable insights (patterns, trends, relationships) that we seek to extract from our data through machine learning and data science. Datasphere manages and integrates structured, semi-structured, and unstructured data types.

Data Warehouse 325

Data Warehouse Metadata Digital Transformation Unstructured Data 325