Jet Global

OCTOBER 30, 2020

Introducing Data Lakes. Microsoft’s next option is called Azure Data Lake Services (ADLS), and it seems to be the company’s favored long-term solution to its D365 F&SCM reporting challenge. Data lake” is a generic term that refers to a fairly new development in the world of big data analytics.

Data Lake 52

Data Lake Unstructured Data Reporting Finance 52

AWS Big Data

MARCH 25, 2024

Studio notebooks seamlessly combine these technologies to make advanced analytics on data streams accessible to developers of all skill sets. Both engines provide native ingestion support from Kinesis Data Streams and Amazon MSK via a separate streaming pipeline to a data lake or data warehouse for analysis.

Data Lake 86

Data Lake Unstructured Data Management Modeling 86

AWS Big Data

MARCH 7, 2023

A data hub contains data at multiple levels of granularity and is often not integrated. It differs from a data lake by offering data that is pre-validated and standardized, allowing for simpler consumption by users. Data hubs and data lakes can coexist in an organization, complementing each other.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68

IBM Big Data Hub

JULY 5, 2022

In today’s world of complex data architectures and emerging technologies, databases can sometimes be undervalued and unrecognized. IBM has been the pioneer in paving the way for data management technologies and advancements for decades, from the first commercial database to quantum computing systems.

Data Lake 97

Data Lake Data Warehouse Publishing Structured Data 97

AWS Big Data

JUNE 6, 2023

SumUp is a leading global financial technology company driven by the purpose of leveling the playing field for small businesses. Unless, of course, the rest of their data also resides in the Google Cloud. AWS Glue gave us a cost-efficient option to migrate the data and we further optimized storage cost by pruning cold data.

Analytics 55

Analytics Data Lake Testing Optimization 55

AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. This may lead to misleading evaluations about the technology or concept being tested.

Testing 96

Testing Data Warehouse Metrics Cost-Benefit 96

AWS Big Data

MARCH 28, 2023

As organizations across the globe are modernizing their data platforms with data lakes on Amazon Simple Storage Service (Amazon S3), handling SCDs in data lakes can be challenging.

Data Lake 68

Data Lake Testing Snapshot Sales 68

Sisense

APRIL 26, 2020

Structured vs unstructured data. Structured data is far easier for programs to understand, while unstructured data poses a greater challenge. However, both types of data play an important role in data analysis. Structured data. Structured data is organized in tabular format (ie.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

AWS Big Data

APRIL 20, 2023

Customers use Amazon Redshift to run their business-critical analytics on petabytes of structured and semi-structured data. Apache Spark enables you to build applications in a variety of languages, such as Java, Scala, and Python, by accessing the data in your Amazon Redshift data warehouse.

Data Lake 73

Data Lake Data Warehouse Sales Data-driven 73

AWS Big Data

NOVEMBER 9, 2023

This process has been scheduled to run daily, ensuring a consistent batch of fresh data for analysis. AWS Glue – AWS Glue is used to load files into Amazon Redshift through the S3 data lake. You can also use features like auto-copy from Amazon S3 (feature under preview) to ingest data from Amazon S3 to Amazon Redshift.

Data Warehouse 100

Data Warehouse Testing Data Quality Reporting 100

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

BizAcuity

MARCH 1, 2019

Data is only useful when it is actionable for which it needs to be supplemented with context and creativity. Traditional methods of analyzing structured data are not designed to efficiently process these large amounts of real-time data that is collected from IoT devices. IoT produces a treasure trove of big data.

IoT 56

IoT Internet of Things Big Data Data-driven 56

IBM Big Data Hub

APRIL 24, 2023

Innovative organizations sought modern solutions to manage larger data capacities and attain secure storage solutions, helping them meet consumer demands. One of these advances included the accelerated adoption of modernized data warehousing technologies. Modern data warehousing technology can handle all data forms.

Data Warehouse 99

Data Warehouse Data Lake Cost-Benefit Enterprise 99

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.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Data Quality 119

AWS Big Data

FEBRUARY 22, 2023

In this post, we show how Ruparupa implemented an incrementally updated data lake to get insights into their business using Amazon Simple Storage Service (Amazon S3), AWS Glue , Apache Hudi , and Amazon QuickSight. An AWS Glue ETL job, using the Apache Hudi connector, updates the S3 data lake hourly with incremental data.

Data Lake 52

Data Lake Dashboards Cost-Benefit Metadata 52

Peter James Thomas

AUGUST 29, 2018

I have since run and driven transformation in Reference Data, Master Data , KYC [3] , Customer Data, Data Warehousing and more recently Data Lakes and Analytics , constantly building experience and capability in the Data Governance , Quality and data services domains, both inside banks, as a consultant and as a vendor.

Data-driven 61

Data-driven Cost-Benefit Metadata Technology 61

CIO Business Intelligence

AUGUST 18, 2022

To find out, he queried Walgreens’ data lakehouse, implemented with Databricks technology on Microsoft Azure. “We For Guadagno, the need to match vaccine availability with patient demand came at the right moment, technologically speaking. based Walgreens consolidated its systems of insight into a single data lakehouse.

Data Lake 140

Data Lake Data Warehouse Unstructured Data Business Intelligence 140

IBM Big Data Hub

JANUARY 18, 2023

In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. It required a different data platform solution. Hence, Data Lake emerged, which handles unstructured and structured data with huge volume. data virtualization) play a key role.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

APRIL 19, 2023

Building an optimal data system As data grows at an extraordinary rate, data proliferation across your data stores, data warehouse, and data lakes can become a challenge. This performance innovation allows Nasdaq to have a multi-use data lake between teams.

Data Warehouse 55

Data Warehouse Data Lake Unstructured Data Optimization 55

AWS Big Data

OCTOBER 25, 2023

Most companies produce and consume unstructured data such as documents, emails, web pages, engagement center phone calls, and social media. By some estimates, unstructured data can make up to 80–90% of all new enterprise data and is growing many times faster than structured data.

Unstructured Data 115

Unstructured Data Metadata Management Analytics 115

AWS Big Data

JANUARY 22, 2024

The solution Acast implemented is a data mesh, architected on AWS. The solution mirrors the organizational structure rather than an explicit architectural decision. As per the Inverse Conway Maneuver , Acast’s technology architecture displays isomorphism with the business architecture.

Data-driven 82

Data-driven Advertising Metadata Data Architecture 82

AWS Big Data

AUGUST 16, 2023

Iceberg manages large collections of files as tables, and it supports modern analytical data lake operations such as record-level insert, update, delete, and time travel queries. Iceberg also helps guarantee data correctness under concurrent write scenarios. We use a sample JSON file as input to Amazon DynamoDB.

Data Lake 68

Data Lake Metadata Testing Snapshot 68

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! Dig into AI.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

AWS Big Data

JULY 12, 2023

Amazon Redshift helps you break down the data silos and allows you to run unified, self-service, real-time, and predictive analytics on all data across your operational databases, data lake, data warehouse, and third-party datasets with built-in governance. Etleap simplifies the data pipeline building experience.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

AWS Big Data

JULY 28, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. It is designed for analyzing large volumes of data and performing complex queries on structured and semi-structured data.

Snapshot 79

Snapshot Metadata Measurement Data Warehouse 79

CDW Research Hub

DECEMBER 4, 2019

Cloud-based data warehouses can also perform complex analytical queries much faster due to the use of massively parallel processing (MPP), which uses multiple processors—each with its own operating system and memory—to simultaneously perform a set of coordinated computations.

Data Warehouse 52

Data Warehouse Data mining Data Lake Dashboards 52

AWS Big Data

APRIL 4, 2024

Amazon Redshift is a recommended service for online analytical processing (OLAP) workloads such as cloud data warehouses, data marts, and other analytical data stores. You can use simple SQL to analyze structured and semi-structured data, operational databases, and data lakes to deliver the best price/performance at any scale.

Big Data 64

Big Data Data Warehouse Advertising OLAP 64

erwin

AUGUST 31, 2023

In today’s fast-paced digital landscape, data reigns supreme. The data-driven enterprise relies on accurate, accessible, and actionable information to make strategic decisions and drive innovation. The benefits Data modeling serves as the blueprint for organizing and structuring data, offering a plethora of benefits.

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

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