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 86

Data Lake Big Data Consulting Data Warehouse 86

Cloudera

JUNE 25, 2021

Using easy-to-define policies, Replication Manager solves one of the biggest barriers for the customers in their cloud adoption journey by allowing them to move both tables/structured data and files/unstructured data to the CDP cloud of their choice easily. CDP Data Lake cluster versions – CM 7.4.0,

Data Lake 71

Data Lake Metadata Unstructured Data Management 71

erwin

AUGUST 31, 2023

Let’s explore the continued relevance of data modeling and its journey through history, challenges faced, adaptations made, and its pivotal role in the new age of data platforms, AI, and democratized data access. Embracing the future In the dynamic world of data, data modeling remains an indispensable tool.

Data-driven 98

Data-driven Modeling Enterprise Structured Data 98

IBM Big Data Hub

APRIL 24, 2023

Benefits of new data warehousing technology Everything is data, regardless of whether it’s structured, semi-structured, or unstructured. Most of the enterprise or legacy data warehousing will support only structured data through relational database management system (RDBMS) databases.

Data Warehouse 92

Data Warehouse Data Lake Cost-Benefit Enterprise 92

AWS Big Data

MAY 28, 2024

The details of each step are as follows: Populate the Amazon Redshift Serverless data warehouse with company stock information stored in Amazon Simple Storage Service (Amazon S3). Redshift Serverless is a fully functional data warehouse holding data tables maintained in real time.

Unstructured Data 72

Unstructured Data Structured Data Data Warehouse Testing 72

CIO Business Intelligence

APRIL 25, 2022

Now generally available, the M&E data lakehouse comes with industry use-case specific features that the company calls accelerators, including real-time personalization, said Steve Sobel, the company’s global head of communications, in a blog post. Features focus on media and entertainment firms.

Recreation/Entertainment 109

Recreation/Entertainment Data Lake Data Warehouse Unstructured Data 109

AWS Big Data

NOVEMBER 22, 2023

Data lakes are designed for storing vast amounts of raw, unstructured, or semi-structured data at a low cost, and organizations share those datasets across multiple departments and teams. The queries on these large datasets read vast amounts of data and can perform complex join operations on multiple datasets.

Statistics 103

Statistics Data Lake Optimization Data-driven 103

Cloudera

DECEMBER 11, 2020

As mentioned in my previous blog on the topic , the recent shift to remote working has seen an increase in conversations around how data is managed. Without meeting GxP compliance, the Merck KGaA team could not run the enterprise data lake needed to store, curate, or process the data required to inform business decisions.

Data Lake 98

Data Lake Cost-Benefit Unstructured Data Data Governance 98

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 fabric and data mesh as concepts have overlaps.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

AWS Big Data

JUNE 6, 2023

This is a guest blog post by Mira Daniels and Sean Whitfield from SumUp. 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. It consists of full-day and intraday tables.

Analytics 55

Analytics Data Lake Testing Optimization 55

IBM Big Data Hub

APRIL 9, 2024

This allows the Masters to scale analytics and AI wherever their data resides, through open formats and integration with existing databases and tools. “Hole distances and pin positions vary from round to round and year to year; these factors are important as we stage the data.”

Management 81

Management IT Machine Learning Metrics 81

Sisense

JULY 22, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways organizations tackle the challenges of this new world to help their companies and their customers thrive. Data modeling: Create relationships between data.

Slice and Dice 98

Slice and Dice Digital Transformation Data Warehouse Data Lake 98

IBM Big Data Hub

APRIL 25, 2023

In a prior blog , we pointed out that warehouses, known for high-performance data processing for business intelligence, can quickly become expensive for new data and evolving workloads. To do so, Presto and Spark need to readily work with existing and modern data warehouse infrastructures.

Optimization 56

Optimization Strategy Data Warehouse Cost-Benefit 56

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 74

Unstructured Data Data Architecture Data Lake Snapshot 74

CIO Business Intelligence

OCTOBER 25, 2023

Zscaler The risks of leveraging AI and ML tools As we discussed in a recent blog , the risks of using generative AI tools in the enterprises are significant. The release of intellectual property and non-public information Generative AI tools can make it easy for well-meaning users to leak sensitive and confidential data.

Enterprise 129

Enterprise Risk Manufacturing Finance 129

IBM Big Data Hub

SEPTEMBER 19, 2023

Overview: Data science vs data analytics Think of data science as the overarching umbrella that covers a wide range of tasks performed to find patterns in large datasets, structure data for use, train machine learning models and develop artificial intelligence (AI) applications.

Data Science 79

Data Science Data Analytics Prescriptive Analytics Analytics 79

IBM Big Data Hub

JULY 5, 2022

Vektis improves healthcare quality through data . Store and query more than just traditional structured data with multi-model capabilities. Seamlessly integrate Db2 with your existing data lake to easily query datasets residing in open data formats like Parquet, Avro and more.

Data Lake 90

Data Lake Data Warehouse Publishing Structured Data 90

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.

Data Governance 52

Data Governance Metadata Cost-Benefit Structured Data 52

Sisense

APRIL 26, 2020

We live in a world of data: there’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. Structured vs unstructured data.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

Cloudera

OCTOBER 7, 2021

In this blog, I will demonstrate the value of Cloudera DataFlow (CDF) , the edge-to-cloud streaming data platform available on the Cloudera Data Platform (CDP) , as a Data integration and Democratization fabric. The post How Cloudera Data Flow Enables Successful Data Mesh Architectures appeared first on Cloudera Blog.

Metadata 124

Metadata Cost-Benefit Enterprise Interactive 124

Cloudera

OCTOBER 30, 2018

In this blog post, Sheryl outlines how next-gen CIP applications are delivering a better customer experience, and why businesses are relying on CIPs as their preferred path to customer insights. Structured data from operational data stores now provides a small slice of the overall data needed to improve customer experience.

Unstructured Data 42

Unstructured Data Data Lake Machine Learning Interactive 42

Sisense

JUNE 30, 2020

Everyone wants to get more out of their data, but how exactly to do that can leave you scratching your head. In a world increasingly dominated by data, users of all kinds are gathering, managing, visualizing, and analyzing data in a wide variety of ways.

Visualization 93

Visualization Analytics Dashboards Data-driven 93

AWS Big Data

JULY 19, 2023

We’ve seen that there is 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 this connector, you can bring the data from Google Cloud Storage to Amazon S3.

Big Data 85

Big Data Software Consulting Unstructured Data 85

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. His expertise lies in constructing robust, scalable, and efficient solutions.

Testing 101

Testing Data Warehouse Metrics Cost-Benefit 101

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 80

Data Lake Data Warehouse Sales Data-driven 80

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

Cloudera

JULY 26, 2021

A common pitfall in the development of data platforms is that they are built around the boundaries of point solutions and are constrained by the technological limitations (e.g., a technology choice such as Spark Streaming is overly focused on throughput at the expense of latency) or data formats (e.g., data warehousing).

Strategy 117

Strategy Data Science Marketing Unstructured Data 117

AWS Big Data

JANUARY 22, 2024

They classified the metrics and indicators in the following categories: Data usage – A clear understanding of who is consuming what data source, materialized with a mapping of consumers and producers. Outside of work, he enjoys traveling and blogging his experiences in social media.

Data-driven 87

Data-driven Advertising Metadata Data Architecture 87

Cloudera

JANUARY 22, 2019

Today’s data landscape is characterized by exponentially increasing volumes of data, comprising a variety of structured, unstructured, and semi-structured data types originating from an expanding number of disparate data sources located on-premises, in the cloud, and at the edge.

Big Data 44

Big Data Data Lake Internet of Things Enterprise 44

AWS Big Data

JULY 12, 2023

This blog post is co-written with Zygimantas Koncius from Etleap. Organizations use their data to extract valuable insights and drive informed business decisions. Amazon Redshift delivers up to five times better price performance than other cloud data warehouses out of the box and helps you keep costs predictable.

Data Warehouse 52

Data Warehouse Modeling Dashboards Data Lake 52

Sisense

OCTOBER 6, 2020

Digging into quantitative data Why is quantitative data important What are the problems with quantitative data Exploring qualitative data Qualitative data benefits Getting the most from qualitative data Better together. This is quantitative data. Qualitative data benefits: Unlocking understanding.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. 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.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

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 56

IoT Internet of Things Big Data Data-driven 56

Ontotext

MARCH 8, 2023

Specifically, the increasing amount of data being generated and collected, and the need to make sense of it, and its use in artificial intelligence and machine learning, which can benefit from the structured data and context provided by knowledge graphs. We get this question regularly.

Enterprise 52

Enterprise Knowledge Discovery Risk Data-driven 52