Sisense

NOVEMBER 12, 2020

Data warehouse vs. databases Traditional vs. Cloud Explained Cloud data warehouses in your data stack A data-driven future powered by the cloud. We live in a world of data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Data warehouse vs. databases.

Data Warehouse 52

Data Warehouse Data Lake OLAP Data-driven 52

AWS Big Data

FEBRUARY 29, 2024

Data governance is a critical building block across all these approaches, and we see two emerging areas of focus. First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses.

Data Governance 99

Data Governance Unstructured Data Metadata Data Lake 99

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.

Data Lake 116

Data Lake Machine Learning Data Warehouse Unstructured Data 116

Smart Data Collective

OCTOBER 27, 2021

The application presents a massive volume of unstructured data through a graphical or programming interface using the analytical abilities of business intelligence technology to provide instant insight. Interactive analytics applications present vast volumes of unstructured data at scale to provide instant insights.

Interactive 112

Interactive Unstructured Data Analytics Data Warehouse 112

AWS Big Data

OCTOBER 20, 2023

Today, we are pleased to announce new AWS Glue connectors for Azure Blob Storage and Azure Data Lake Storage that allow you to move data bi-directionally between Azure Blob Storage, Azure Data Lake Storage, and Amazon Simple Storage Service (Amazon S3). option("header","true").load("wasbs://yourblob@youraccountname.blob.core.windows.net/loadingtest-input/100mb")

Data Lake 87

Data Lake Big Data Consulting Data Warehouse 87

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 117

Data Lake Analytics Dashboards Metrics 117

CIO Business Intelligence

OCTOBER 13, 2023

Solutions data architect: These individuals design and implement data solutions for specific business needs, including data warehouses, data marts, and data lakes. Application data architect: The application data architect designs and implements data models for specific software applications.

Data Architecture 127

Data Architecture Data Warehouse Statistics Visualization 127

CIO Business Intelligence

MAY 24, 2022

The Intelligent Data Management Cloud for Financial Services, like Informatica’s other industry-focused platforms, combines vertical-based accelerators with the company’s suite of machine learning tools to help with challenges around unstructured data and quick data-based decision making. .

Finance 131

Finance Management Metadata Data Quality 131

IBM Big Data Hub

SEPTEMBER 19, 2023

Though you may encounter the terms “data science” and “data analytics” being used interchangeably in conversations or online, they refer to two distinctly different concepts. Meanwhile, data analytics is the act of examining datasets to extract value and find answers to specific questions.

Data Science 82

Data Science Data Analytics Prescriptive Analytics Analytics 82

Jet Global

OCTOBER 30, 2020

SQL is a near-universal language in the world of software applications. We refer to the first as “data entities.” You can think of data entities as a kind of translation layer or gatekeeper. When a software application asks a data entity for information, it is not making a request to the database directly.

Data Lake 52

Data Lake Unstructured Data Reporting Finance 52

Andrew White

DECEMBER 9, 2019

See: Webinar Effective Data and Analytics Governance – Finally! Blog A Little Data Governance Goes a Long Way. I spoke with an IT software vendor about an aspect of data and analytics governance. Scope could be: Data (i.e. Information (processed data). The call was my penultimate inquiry of the week.

Analytics 66

Analytics Data Lake Data Governance Metadata 66

CIO Business Intelligence

SEPTEMBER 21, 2023

They can code, write poetry, draw in any art style, create PowerPoint slides and website mockups, write marketing copy and emails, and find new vulnerabilities in software and plot holes in unpublished novels. In a recent report, he estimated that gen AI software revenues will grow from $3.7 Gen AI took a few months.

Enterprise 128

Enterprise Consulting Modeling Cost-Benefit 128

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. Structured versus unstructured data.

Data Lake 52

Data Lake Data Warehouse Unstructured Data Structured Data 52

AWS Big Data

JANUARY 8, 2024

Stream ingestion – The stream ingestion layer is responsible for ingesting data into the stream storage layer. It provides the ability to collect data from tens of thousands of data sources and ingest in real time. When building event-driven microservices, customers want to achieve 1.

Analytics 116

Analytics IoT Data-driven Snapshot 116

Sisense

OCTOBER 6, 2020

As quantitative data is always numeric, it’s relatively straightforward to put it in order, manage it, analyze it, visualize it, and do calculations with it. Spreadsheet software like Excel, Google Sheets, or traditional database management systems all mainly deal with quantitative data.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Cloudera

AUGUST 21, 2020

Perhaps one of the most significant contributions in data technology advancement has been the advent of “Big Data” platforms. Historically these highly specialized platforms were deployed on-prem in private data centers to ensure greater control , security, and compliance. They are not plug-n-play SaaS applications.

Cost-Benefit 73

Cost-Benefit Big Data ROI Risk 73

CIO Business Intelligence

MARCH 9, 2022

But the data repository options that have been around for a while tend to fall short in their ability to serve as the foundation for big data analytics powered by AI. Traditional data warehouses, for example, support datasets from multiple sources but require a consistent data structure. Meet the data lakehouse.

Data Lake 103

Data Lake Unstructured Data Data Warehouse Data Quality 103

BizAcuity

MAY 10, 2022

VMs are nothing but systems that work as computers (using hardware or software) to provide an additional computational environment for enterprises. Storing data is extremely expensive even with VMs during this time. 2012: Amazon Redshift, the first of its kind cloud-based data warehouse service comes into existence.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

BizAcuity

APRIL 14, 2022

A large number of organizations accumulate massive amounts of data almost every single day and analyzing every batch of data that comes in demands the use of modern tools and platforms. The best way to avoid poor data quality is having a strict data governance system in place. Unstructured Data Management.

Big Data 52

Big Data Data Analytics Management Unstructured Data 52

Sisense

JULY 22, 2020

The trend has been towards using cloud-based applications and tools for different functions, such as Salesforce for sales, Marketo for marketing automation, and large-scale data storage like AWS or data lakes such as Amazon S3 , Hadoop and Microsoft Azure. Sisense provides instant access to your cloud data warehouses.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

Sisense

MAY 11, 2021

The reasons for this are simple: Before you can start analyzing data, huge datasets like data lakes must be modeled or transformed to be usable. According to a recent survey conducted by IDC , 43% of respondents were drawing intelligence from 10 to 30 data sources in 2020, with a jump to 64% in 2021!

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Sisense

JULY 6, 2021

Product, technology, and R&D professionals are always keen to discuss how software companies are driving product innovation and new revenue streams through embedded analytics. To drive this point home, Yonatan Dolan, an Analytics Specialist from AWS, introduced AWS’ new Lake House architecture.

Data Lake 52

Data Lake Data Warehouse Data-driven Unstructured Data 52

Jet Global

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

NOVEMBER 21, 2023

To have any hope of generating value from growing data sets, enterprise organizations must turn to the latest technology. You’ve heard of data warehouses, and probable data lakes, but now, the data lakehouse is emerging as the new corporate buzzword. To address this, the data lakehouse was born.

Data Lake 52

Data Lake Data Warehouse Reporting Enterprise 52