Analytics Vidhya

FEBRUARY 25, 2023

Introduction A data lake is a centralized and scalable repository storing structured and unstructured data. The need for a data lake arises from the growing volume, variety, and velocity of data companies need to manage and analyze.

Data Lake 178

Data Lake Unstructured Data Management Analytics 178

CIO Business Intelligence

OCTOBER 19, 2023

Enterprises can harness the power of continuous information flow by lessening the gap between traditional architecture and dynamic data streams. Unstructured data formatting issues Increasing data volume gets more challenging because it has large volumes of unstructured data.

Data Integration 126

Data Integration Unstructured Data Data-driven Data Warehouse 126

CIO Business Intelligence

AUGUST 18, 2022

Traditionally, organizations have maintained two systems as part of their data strategies: a system of record on which to run their business and a system of insight such as a data warehouse from which to gather business intelligence (BI). You can intuitively query the data from the data lake.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

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

JUNE 11, 2024

By leveraging an organization’s proprietary data, GenAI models can produce highly relevant and customized outputs that align with the business’s specific needs and objectives. Structured data is highly organized and formatted in a way that makes it easily searchable in databases and data warehouses.

Enterprise 93

Enterprise Unstructured Data Contextual Data Data-driven 93

Cloudera

NOVEMBER 25, 2020

Sample and treatment history data is mostly structured, using analytics engines that use well-known, standard SQL. Interview notes, patient information, and treatment history is a mixed set of semi-structured and unstructured data, often only accessed using proprietary, or less known, techniques and languages.

Data Warehouse 59

Data Warehouse Unstructured Data Analytics Visualization 59

AWS Big Data

APRIL 19, 2023

In this post, we look at three key challenges that customers face with growing data and how a modern data warehouse and analytics system like Amazon Redshift can meet these challenges across industries and segments. However, these wide-ranging data types are typically stored in silos across multiple data stores.

Data Warehouse 58

Data Warehouse Data Lake Unstructured Data Optimization 58

CIO Business Intelligence

APRIL 25, 2022

The data lakehouse is a relatively new data architecture concept, first championed by Cloudera, which offers both storage and analytics capabilities as part of the same solution, in contrast to the concepts for data lake and data warehouse which, respectively, store data in native format, and structured data, often in SQL format.

Recreation/Entertainment 119

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 119

CIO Business Intelligence

APRIL 25, 2024

Currently, a handful of startups offer “reverse” extract, transform, and load (ETL), in which they copy data from a customer’s data warehouse or data platform back into systems of engagement where business users do their work. Sharing Customer 360 insights back without data replication.

Data Integration 119

Data Integration Data Lake Data Warehouse Metadata 119

AWS Big Data

FEBRUARY 26, 2025

Amazon SageMaker Lakehouse provides an open data architecture that reduces data silos and unifies data across Amazon Simple Storage Service (Amazon S3) data lakes, Redshift data warehouses, and third-party and federated data sources. AWS Glue 5.0 Finally, AWS Glue 5.0

Analytics 60

Analytics Data Lake Metadata Data Warehouse 60

CIO Business Intelligence

OCTOBER 2, 2024

Collect, filter, and categorize data The first is a series of processes — collecting, filtering, and categorizing data — that may take several months for KM or RAG models. Structured data is relatively easy, but the unstructured data, while much more difficult to categorize, is the most valuable.

Management 141

Management Data Governance Cost-Benefit Structured Data 141

Jet Global

NOVEMBER 5, 2020

OLAP reporting has traditionally relied on a data warehouse. Again, this entails creating a copy of the transactional data in the ERP system, but it also involves some preprocessing of data into so-called “cubes” so that you can retrieve aggregate totals and present them much faster.

Data Lake 98

Data Lake OLAP Data Warehouse Unstructured Data 98

CIO Business Intelligence

FEBRUARY 16, 2023

The Basel, Switzerland-based company, which operates in more than 100 countries, has petabytes of data, including highly structured customer data, data about treatments and lab requests, operational data, and a massive, growing volume of unstructured data, particularly imaging data.

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Data Warehouse 105

CIO Business Intelligence

MARCH 29, 2024

Modernizing data operations CIOs like Woodring know well that the quality of an AI model depends in large part on the quality of the data involved — and how that data is injected from databases, data warehouses, cloud data lakes, and the like into large language models.

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Data Lake Machine Learning Data Warehouse Unstructured Data 134

Jet Global

SEPTEMBER 4, 2020

For more sophisticated multidimensional reporting functions, however, a more advanced approach to staging data is required. The Data Warehouse Approach. Data warehouses gained momentum back in the early 1990s as companies dealing with growing volumes of data were seeking ways to make analytics faster and more accessible.

Data Lake 88

Data Lake OLAP Data Warehouse Unstructured Data 88

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

AWS Big Data

JUNE 26, 2024

New feature: Custom AWS service blueprints Previously, Amazon DataZone provided default blueprints that created AWS resources required for data lake, data warehouse, and machine learning use cases. You can build projects and subscribe to both unstructured and structured data assets within the Amazon DataZone portal.

Data Lake 117

Data Lake Data Warehouse Unstructured Data Data Governance 117

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.,

Metadata 132

Metadata Cost-Benefit Measurement Data-driven 132

Octopai

MARCH 22, 2023

Data migration can be a daunting task, especially when dealing with large volumes of data. Snowflake is one of the leading cloud-based data warehouse that provides scalability, flexibility, and ease of use. Snowflake data warehouse platform has been designed to leverage the power of modern-day cloud computing technology.

Data Warehouse 103

Data Warehouse Cost-Benefit Unstructured Data Optimization 103

Cloudera

APRIL 1, 2024

We scored the highest in hybrid, intercloud, and multi-cloud capabilities because we are the only vendor in the market with a true hybrid data platform that can run on any cloud including private cloud to deliver a seamless, unified experience for all data, wherever it lies.

Unstructured Data 105

Unstructured Data Cost-Benefit Metadata Machine Learning 105

Analytics Vidhya

MAY 29, 2023

The two pillars of data analytics include data mining and warehousing. They are essential for data collection, management, storage, and analysis. Both are associated with data usage but differ from each other.

Data mining 307

Data mining Data Collection Strategy Data Analytics 307

FineReport

JUNE 24, 2021

Technicals such as data warehouse, online analytical processing (OLAP) tools, and data mining are often binding. On the opposite, it is more of a comprehensive application of data warehouse, OLAP, data mining, and so forth. All BI software capabilities, functionalities, and features focus on data.

Business Intelligence 84

Business Intelligence OLAP Data mining Visualization 84

Cloudera

SEPTEMBER 12, 2022

First, organizations have a tough time getting their arms around their data. More data is generated in ever wider varieties and in ever more locations. Organizations don’t know what they have anymore and so can’t fully capitalize on it — the majority of data generated goes unused in decision making.

Unstructured Data 75

Unstructured Data Data Architecture Data Lake Snapshot 75

Sisense

OCTOBER 6, 2020

Most commonly, we think of data as numbers that show information such as sales figures, marketing data, payroll totals, financial statistics, and other data that can be counted and measured objectively. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?”

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Sisense

JUNE 30, 2020

The data drawn from power visualizations comes from a variety of sources: Structured data , in the form of relational databases such as Excel, or unstructured data, deriving from text, video, audio, photos, the internet and smart devices.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

IBM Big Data Hub

SEPTEMBER 19, 2023

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

Data Science 76

Data Science Data Analytics Prescriptive Analytics Analytics 76

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.

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Data Lake Big Data Data Warehouse Consulting 110

AWS Big Data

MARCH 25, 2024

This data store provides your organization with the holistic customer records view that is needed for operational efficiency of RAG-based generative AI applications. For building such a data store, an unstructured data store would be best. This is typically unstructured data and is updated in a non-incremental fashion.

Data Lake 120

Data Lake Unstructured Data Management Snapshot 120

Ontotext

DECEMBER 15, 2022

Connecting the dots of data of all types. To begin with, Fantastic Finserv has to handle a wide variety of data. This includes traditional structured data such as: Reference data – the data used to relate data to information outside of the organization.

Metadata 52

Metadata Unstructured Data Structured Data Enterprise 52

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 first challenge here is how to enable agile enterprise information management.

Enterprise 59

Enterprise B2B Unstructured Data Machine Learning 59

Sisense

MAY 11, 2021

We’re going to nerd out for a minute and dig into the evolving architecture of Sisense to illustrate some elements of the data modeling process: Historically, the data modeling process that Sisense recommended was to structure data mainly to support the BI and analytics capabilities/users.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Jet Global

OCTOBER 30, 2020

Data lakes are oriented toward unstructured data and artificial intelligence. What are unstructured data? First, let’s consider what “structured” data looks like: CustomerID. Structured data are, by their very nature, orderly and predictable. ERP data are highly structured.

Data Lake 52

Data Lake Unstructured Data Reporting Finance 52

Cloudera

NOVEMBER 15, 2024

Unstructured data not ready for analysis: Even when defenders finally collect log data, it’s rarely in a format that’s ready for analysis. Cyber logs are often unstructured or semi-structured, making it difficult to derive insights from them.

Analytics 59

Analytics Metadata Snapshot Data-driven 59

FineReport

DECEMBER 27, 2021

Enterprise BI typically functions by combining enterprise data warehouse and enterprise license to a BI platform or toolset that business users in various roles can use. Usually, enterprise BI incorporates relatively rigid, well-structured data models on data warehouses or data marts.

Enterprise 59

Enterprise Dashboards Business Intelligence Visualization 59

Wayne Yaddow

MARCH 14, 2025

Testing Limitations: Both dbt Cloud and dbtCore dbt is designed for SQL-based transformations in data warehouses, meaning it is not well-suited for non-SQL, real-time, or highly complex unstructured data transformations. Workaround: Use Git branches, tagging, and commit messages to trackchanges.

Data Transformation 52

Data Transformation Testing Unstructured Data Data Quality 52

Sisense

MARCH 14, 2021

Looking at the diagram, we see that Business Intelligence (BI) is a collection of analytical methods applied to big data to surface actionable intelligence by identifying patterns in voluminous data. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

AWS Big Data

FEBRUARY 22, 2023

Data analytic challenges As an ecommerce company, Ruparupa produces a lot of data from their ecommerce website, their inventory systems, and distribution and finance applications. The data can be structured data from existing systems, and can also be unstructured or semi-structured data from their customer interactions.

Data Lake 52

Data Lake Dashboards Cost-Benefit Data Warehouse 52