DataKitchen

DECEMBER 7, 2021

This book is not available until January 2022, but considering all the hype around the data mesh, we expect it to be a best seller. In the book, author Zhamak Dehghani reveals that, despite the time, money, and effort poured into them, data warehouses and data lakes fail when applied at the scale and speed of today’s organizations.

Data-driven 246

Data-driven Data Governance Big Data Data Science 246

DataKitchen

AUGUST 19, 2021

Figure 3 shows an example processing architecture with data flowing in from internal and external sources. Each data source is updated on its own schedule, for example, daily, weekly or monthly. The data scientists and analysts have what they need to build analytics for the user. The new Recipes run, and BOOM! Conclusion.

Data Warehouse 246

Data Warehouse Data Lake Manufacturing Testing 246

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 101

Data Lake Testing Snapshot Big Data 101

Jen Stirrup

MAY 5, 2020

Recently, I gave a Make Your Data Work Monday webinar on the complexities of the data sources for data science in Azure, and I thought it important enough to turn into an actual post. How can you differentiate the different opportunities to store your data in Azure?

Machine Learning 89

Machine Learning Data Science Data Lake Big Data 89

CIO Business Intelligence

MARCH 9, 2022

Applying artificial intelligence (AI) to data analytics for deeper, better insights and automation is a growing enterprise IT priority. 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.

Data Lake 119

Data Lake Unstructured Data Data Warehouse Big Data 119

DataKitchen

AUGUST 9, 2021

Instead of having a giant, unwieldy data lake , the data mesh breaks up the data and workflow assets into controllable and composable domains with inherent interdependencies. Domains are built from raw data and/or the output of other domains.

Testing 246

Testing Data Lake Metadata Publishing 246

AWS Big Data

AUGUST 3, 2023

With the rapid growth of technology, more and more data volume is coming in many different formats—structured, semi-structured, and unstructured. Data analytics on operational data at near-real time is becoming a common need. Then we can query the data with Amazon Athena visualize it in Amazon QuickSight.

Data Lake 98

Data Lake Visualization Dashboards Insurance 98

DataKitchen

JANUARY 3, 2022

A DataOps process hub offers a way for business analytics teams to cope with fast-paced requirements without expanding staff or sacrificing quality. Analytics Hub and Spoke. The data analytics function in large enterprises is generally distributed across departments and roles. DataOps Process Hub.

Business Analytics 245

Business Analytics Analytics Testing Dashboards 245

CIO Business Intelligence

NOVEMBER 25, 2022

Carhartt’s signature workwear is near ubiquitous, and its continuing presence on factory floors and at skate parks alike is fueled in part thanks to an ongoing digital transformation that is advancing the 133-year-old Midwest company’s operations to make the most of advanced digital technologies, including the cloud, data analytics, and AI.

Data Lake 128

Data Lake Data Warehouse Unstructured Data Data Architecture 128

AWS Big Data

NOVEMBER 7, 2024

This post explores how you can use BladeBridge , a leading data environment modernization solution, to simplify and accelerate the migration of SQL code from BigQuery to Amazon Redshift. Tens of thousands of customers use Amazon Redshift every day to run analytics, processing exabytes of data for business insights.

Data Warehouse 105

Data Warehouse Reporting Big Data Data Lake 105

CIO Business Intelligence

JUNE 29, 2022

And as businesses contend with increasingly large amounts of data, the cloud is fast becoming the logical place where analytics work gets done. For many enterprises, Microsoft Azure has become a central hub for analytics. Azure Data Explorer. Azure Data Lake Analytics.

Data Lake 116

Data Lake Analytics Data Warehouse Machine Learning 116

AWS Big Data

DECEMBER 4, 2024

In today’s data-driven world , organizations are constantly seeking efficient ways to process and analyze vast amounts of information across data lakes and warehouses. This post will showcase how this data can also be queried by other data teams using Amazon Athena. Verify that you have Python version 3.7

Data Lake 116

Data Lake Metadata Insurance Data-driven 116

AWS Big Data

APRIL 18, 2024

The Salesforce Trust Intelligence Platform (TIP) log platform team is responsible for data pipeline and data lake infrastructure, providing log ingestion, normalization, persistence, search, and detection capability to ensure Salesforce is safe from threat actors. This is the bronze layer of the TIP data lake.

Optimization 111

Optimization Data Lake Management Key Performance Indicator 111

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift is a fully managed data warehousing service that offers both provisioned and serverless options, making it more efficient to run and scale analytics without having to manage your data warehouse. These upstream data sources constitute the data producer components.

Data Warehouse 111

Data Warehouse Analytics Data Lake Data Science 111

CDW Research Hub

JULY 18, 2022

One modern data platform solution that provides simplicity and flexibility to grow is Snowflake’s data cloud and platform. These Snowflake accelerators reduce the time to analytics for your users at all levels so you can make data-driven decisions faster. Security Data Lake. Snowflake Health Check.

Optimization 87

Optimization Data Lake Data Warehouse Manufacturing 87

DataKitchen

JUNE 12, 2023

We had been talking about “Agile Analytic Operations,” “DevOps for Data Teams,” and “Lean Manufacturing For Data,” but the concept was hard to get across and communicate. I spent much time de-categorizing DataOps: we are not discussing ETL, Data Lake, or Data Science.

Testing 130

Testing Dashboards Data Lake Data Science 130

CIO Business Intelligence

JUNE 23, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 98

Data Lake Data Warehouse Machine Learning Data-driven 98

AWS Big Data

NOVEMBER 6, 2023

Amazon EMR Studio is an integrated development environment (IDE) that makes it straightforward for data scientists and data engineers to develop, visualize, and debug data engineering and data science applications written in R, Python, Scala, and PySpark. This helps you reduce operational overhead.

Data Lake 111

Data Lake Sales Management Testing 111

Cloudera

JUNE 18, 2022

Cloudera customers run some of the biggest data lakes on earth. These lakes power mission critical large scale data analytics, business intelligence (BI), and machine learning use cases, including enterprise data warehouses. On data warehouses and data lakes.

Data Lake 94

Data Lake Data Warehouse Machine Learning Data-driven 94

AWS Big Data

NOVEMBER 8, 2023

This post was co-written with Rajiv Arora, Director of Data Science Platform at Gilead Life Sciences. Gilead Sciences, Inc. Create a data lake external schema and table in Redshift Serverless. You can query data lake tables directly from Amazon Redshift Query Editor v2 or your favorite SQL editors.

Data Lake 104

Data Lake Data Warehouse Cost-Benefit Optimization 104

Data Virtualization

JANUARY 19, 2023

Reading Time: 2 minutes Today, many businesses are modernizing their on-premises data warehouses or cloud-based data lakes using Microsoft Azure Synapse Analytics. Unfortunately, with data spread.

Data Analytics 52

Data Analytics Data Lake Data Warehouse Analytics 52

CIO Business Intelligence

JULY 24, 2022

He announced his departure on LinkedIn and reflected on some of the achievements during the five years with the department which included building an advanced data analytics platforms utilising data warehouse, a data lake, data science containers and supporting visualisation tools. IT Leadership

IT 98

IT Data Lake Data Warehouse Digital Transformation 98

Cloudera

NOVEMBER 18, 2020

It hosts over 150 big data analytics sandboxes across the region with over 200 users utilizing the sandbox for data discovery. With this functionality, business units can now leverage big data analytics to develop better and faster insights to help achieve better revenues, higher productivity, and decrease risk. .

Internet Publishing and Broadcasting 123

Internet Publishing and Broadcasting Data-driven Broadcasting Digital Transformation 123

CIO Business Intelligence

AUGUST 3, 2023

When global technology company Lenovo started utilizing data analytics, they helped identify a new market niche for its gaming laptops, and powered remote diagnostics so their customers got the most from their servers and other devices. Without those templates, it’s hard to add such information after the fact.”

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

Cloudera

JULY 9, 2018

Most organizations struggle to unlock data science in the enterprise. To that end, Cloudera offers the Data Science Workbench, a collaborative, scalable, and highly extensible platform for data exploration, analysis, modeling, and visualization. That friction is what defines the new data science iron triangle.

Machine Learning 42

Machine Learning Data Science Visualization Business Intelligence 42

Cloudera

JANUARY 18, 2022

With a solution based on Cloudera Data Science Workbench (CDSW), the bank implemented a more streamlined loan approval process that reduced processing time from a week to just hours. As a result of this innovative data solution, the company helped customers while keeping its default rate low. .

Data Lake 96

Data Lake Digital Transformation Data-driven Dashboards 96

IBM Big Data Hub

SEPTEMBER 25, 2023

Presto was able to achieve this level of scalability by completely separating analytical compute from data storage. Presto is an open source distributed SQL query engine for data analytics and the data lakehouse, designed for running interactive analytic queries against datasets of all sizes, from gigabytes to petabytes.

OLAP 86

OLAP Data Lake Data-driven Online Analytical Processing 86

IBM Big Data Hub

OCTOBER 4, 2023

Another IDC study showed that while 2/3 of respondents reported using AI-driven data analytics, most reported that less than half of the data under management is available for this type of analytics. from 2022 to 2026.

Data Lake 77

Data Lake Metadata Data Warehouse Cost-Benefit 77

AWS Big Data

OCTOBER 25, 2023

Therefore, there is a need to being able to analyze and extract value from the data economically and flexibly. Solution overview Data and metadata discovery is one of the primary requirements in data analytics, where data consumers explore what data is available and in what format, and then consume or query it for analysis.

Unstructured Data 133

Unstructured Data Metadata Management Analytics 133

AWS Big Data

AUGUST 19, 2024

The secure connectivity pattern prevents data transfers over the public internet, enhancing data privacy and security. Combining AWS data integration services like AWS Glue with data platforms like Snowflake allows you to build scalable, secure data lakes and pipelines to power analytics, BI, data science, and ML use cases.

Analytics 119

Analytics Data-driven Data Integration Data Lake 119

Cloudera

JUNE 16, 2022

CSP was recently recognized as a leader in the 2022 GigaOm Radar for Streaming Data Platforms report. Building real-time data analytics pipelines is a complex problem, and we saw customers struggle using processing frameworks such as Apache Storm, Spark Streaming, and Kafka Streams. . Without context, streaming data is useless.”

Data Lake 88

Data Lake Manufacturing Metadata Dashboards 88

AWS Big Data

AUGUST 6, 2024

In essence, it’s the foundation for user-centric data analysis in modern apps, because it’s the layer that translates technical assets into business-friendly terms that enable users to extract actionable insights from data. The scope of data analytics has grown, and more user personas are now seeking to extract insights themselves.

OLAP 110

OLAP Analytics Visualization Dashboards 110

IBM Big Data Hub

JANUARY 17, 2023

A data lakehouse is an emerging data management architecture that improves efficiency and converges data warehouse and data lake capabilities driven by a need to improve efficiency and obtain critical insights faster. Let’s start with why data lakehouses are becoming increasingly important.

Data Lake 52

Data Lake Metadata Data Warehouse Data Governance 52

AWS Big Data

MAY 16, 2024

This partnership truly aligns with our vision for smarter, data-driven decision-making,” says the Data Science Team at Aramex. About Amazon Redshift Thousands of customers rely on Amazon Redshift to analyze data from terabytes to petabytes and run complex analytical queries. To learn more, visit CARTO.

Data Warehouse 119

Data Warehouse Visualization Cost-Benefit Data-driven 119

AWS Big Data

MARCH 26, 2024

The AWS modern data architecture shows a way to build a purpose-built, secure, and scalable data platform in the cloud. Learn from this to build querying capabilities across your data lake and the data warehouse. About the Authors Ismail Makhlouf is a Senior Specialist Solutions Architect for Data Analytics at AWS.

Data Strategy 99

Data Strategy Strategy Data Warehouse Prescriptive Analytics 99

Andrew White

DECEMBER 9, 2019

Scope could be: Data (i.e. Information (processed data). Analytic (the analytics itself). Records (files, or what you might all unstructured data). Analytical stewardship is a missing link in analytics, BI and data science. Images (i.e. Events or transactions.

Analytics 66

Analytics Data Lake Data Governance Data Warehouse 66

Alation

AUGUST 4, 2022

Many CIOs argue the rise of big data pushed people to use data more proactively for business decision-making. Big data got“ more leaders and people in the organization to use data, analytics, and machine learning in their decision making,” says former CIO Isaac Sacolick. Big data can grow too big fast.

Big Data 95

Big Data Digital Transformation Data Lake Data-driven 95