erwin

AUGUST 15, 2022

For NoSQL, data lakes, and data lake houses—data modeling of both structured and unstructured data is somewhat novel and thorny. This blog is an introduction to some advanced NoSQL and data lake database design techniques (while avoiding common pitfalls) is noteworthy. Data modeling basics.

Data Lake 52

Data Lake Modeling Unstructured Data Data Warehouse 52

Ontotext

DECEMBER 15, 2022

Most legacy approaches to data management, like relational databases and data warehouses, focus on structured data. But in the modern world, more and more data comes from unstructured sources, and here’s where knowledge graphs gain the upper hand.

Metadata 52

Metadata Unstructured Data Structured Data Enterprise 52

erwin

JUNE 26, 2020

Given the value this sort of data-driven insight can provide, the reason organizations need a data catalog should become clearer. It’s no surprise that most organizations’ data is often fragmented and siloed across numerous sources (e.g., Clearly documents data catalog policies, rules and shares information assets.

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

Ontotext

MARCH 18, 2020

According to an article in Harvard Business Review , cross-industry studies show that, on average, big enterprises actively use less than half of their structured data and sometimes about 1% of their unstructured data. The many data warehouse systems designed in the last 30 years present significant difficulties in that respect.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

CIO Business Intelligence

SEPTEMBER 21, 2023

ML was used for sentiment analysis, and to scan documents, classify images, transcribe recordings, and other specific functions. One of the best immediate use cases is summarizing documents and extracting information from material, he says. But it’ll enable people to do higher-value work than they are currently able to do.”

Enterprise 130

Enterprise Consulting Modeling Cost-Benefit 130

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 80

Data Lake Big Data Consulting Data Warehouse 80

Sisense

MARCH 20, 2019

MongoDB (or NoSQL) : An open source Database Management System (DBMS), MongoDB uses a document-oriented database model. That means that instead of using tables in rows in a database, MongoDB is made up of collections of documents. Get ready data engineers, now you need to have both AWS and Microsoft Azure to be considered up-to-date.

Big Data 72

Big Data Machine Learning Data Warehouse Unstructured Data 72

Smart Data Collective

JUNE 7, 2019

We’ll also deal with how big data stream processing can help new emerging markets in the world. What is Big Data? Big Data is defined as a large volume of structured and unstructured data that a business comes across their day-to-day operations. However, the amount of data isn’t really a big deal.

Big Data 81

Big Data Marketing Cost-Benefit Unstructured Data 81

AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 109

Data Lake Analytics Dashboards Metrics 109

Sisense

APRIL 9, 2021

Until then though, they don’t necessarily want to spend the time and resources necessary to create a schema to house this data in a traditional data warehouse. Instead, businesses are increasingly turning to data lakes to store massive amounts of unstructured data. The rise of data warehouses and data lakes.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Structured Data 52

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 57

Data Warehouse Unstructured Data Analytics Visualization 57

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

Domino Data Lab

JULY 2, 2019

The authors of AutoPandas observed that: The APIs for popular data science packages tend to have relatively steep learning curves. People look toward online resources such as StackOverflow to find out how to use APIs when the documentation doesn’t have an example that fits. Instead, program synthesis can address these issues.

Metadata 105

Metadata Machine Learning Data Science Data-driven 105

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 99

Metadata Visualization Unstructured Data Data mining 99

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 109

Data Lake Metadata Optimization Statistics 109

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

IBM Big Data Hub

AUGUST 1, 2023

Fortunately, data stores serve as secure data repositories and enable foundation models to scale in both terms of their size and their training data. Data stores suitable for business-focused generative AI are built on an open lakehouse architecture, combining the qualities of a data lake and data warehouse.

Modeling 59

Modeling Cost-Benefit Data Lake Machine Learning 59

Alation

APRIL 6, 2023

Data governance is traditionally applied to structured data assets that are most often found in databases and information systems. This blog focuses on governing spreadsheets that contain data, information, and metadata, and must themselves be governed. There are others that consider spreadsheets to be trouble.

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 52

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. Connect tables.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

IBM Big Data Hub

MAY 17, 2023

Data Fabric DaaS is built on CP4D that, together with Data Fabric, allows Data Virtualization which procures data from surround systems (such as data warehouses) and generates insights on the fly. MVI and CP4D together empower DaaS by providing an edge in visual inspection and foreseeing challenges.

Data Collection 82

Data Collection Visualization Data-driven Unstructured Data 82

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? This should also include creating a plan for data storage services. Define a budget.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

Alation

AUGUST 4, 2022

“File-based storage of data is the norm even under more relational models. [In In the cloud], Graph databases, document stores, file stores, relational stores all now exist, each addressing different challenges.” In this way, the cloud has democratized access to some of the best outputs of big data.

Big Data 95

Big Data Digital Transformation Data Lake Data-driven 95

Jet Global

NOVEMBER 7, 2023

This growth is caused, in part, by the increasing use of cloud platforms for data storage and processing. But it is also a result of the surge in multimedia content in cloud repositories that requires tools and methods for extracting insights from rich, unstructured data formats.

Enterprise 52

Enterprise Data Warehouse Operational Reporting Reporting 52