CIO Business Intelligence

JULY 26, 2023

But Cox and Djuric do know that 82% of Keller Williams’ agent have been active on the homegrown CRM application in the past 90 days and can deduce the high value of their data from that statistic alone.

Data Lake 98

Data Lake Digital Transformation Machine Learning Data Architecture 98

Cloudera

JUNE 25, 2021

This blog post outlines detailed step by step instructions to perform Hive Replication from an on-prem CDH cluster to a CDP Public Cloud Data Lake. CDP Data Lake cluster versions – CM 7.4.0, Pre-Check: Data Lake Cluster. Understanding Ranger Policies in Data Lake Cluster. Runtime 7.2.8.

Data Lake 68

Data Lake Metadata Unstructured Data Management 68

AWS Big Data

NOVEMBER 20, 2023

Use case A typical workload for AWS Glue for Apache Spark jobs is to load data from a relational database to a data lake with SQL-based transformations. On the Graphed metrics tab, configure your preferred statistic, period, and so on. When the example job ran, the workerUtilization metrics showed the following trend.

Metrics 92

Metrics Data Lake Cost-Benefit Dashboards 92

CIO Business Intelligence

MAY 12, 2022

The tools include sophisticated pipelines for gathering data from across the enterprise, add layers of statistical analysis and machine learning to make projections about the future, and distill these insights into useful summaries so that business users can act on them. On premises or in SAP cloud. Per user, per month. Free tier.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

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 89

Data Science Data Analytics Prescriptive Analytics Analytics 89

DataKitchen

NOVEMBER 18, 2022

With this information in a shared context, your analyst working on a data lake will know if the 15 datasets she is viewing are accurate, the most recent, or of the same date range. And she’ll know when newer data will arrive. By setting process expectations, journeys can identify variances in each pipeline run.

Testing 130

Testing Statistics Measurement Metrics 130

AWS Big Data

SEPTEMBER 13, 2023

A modern data architecture is an evolutionary architecture pattern designed to integrate a data lake, data warehouse, and purpose-built stores with a unified governance model. The company wanted the ability to continue processing operational data in the secondary Region in the rare event of primary Region failure.

Data Lake 87

Data Lake Data Processing Metadata Snapshot 87

Peter James Thomas

AUGUST 18, 2018

That was the Science, here comes the Technology… A Brief Hydrology of Data Lakes. Even back then, these were used for activities such as Analytics , Dashboards , Statistical Modelling , Data Mining and Advanced Visualisation. This is the essence of Convergent Evolution.

Data Lake 63

Data Lake Data Warehouse Data mining Statistics 63

AWS Big Data

AUGUST 31, 2023

Amazon Redshift enables you to directly access data stored in Amazon Simple Storage Service (Amazon S3) using SQL queries and join data across your data warehouse and data lake. With Amazon Redshift, you can query the data in your S3 data lake using a central AWS Glue metastore from your Redshift data warehouse.

Data Lake 89

Data Lake Data Warehouse Metadata Data Architecture 89

Timo Elliott

JUNE 19, 2023

All of the statistics from IDC and the others show that there’s a massive market for digital services. The next area is data. There’s a huge disruption around data. Increasingly now, we can bring the technology to the data rather than the other way around. The first is the new digital opportunities.

Data Lake 105

Data Lake Digital Transformation Recreation/Entertainment Technology 105

FineReport

MARCH 24, 2024

Data analysts contribute value to organizations by uncovering trends, patterns, and insights through data gathering, cleaning, and statistical analysis. They identify and interpret trends in complex datasets, optimize statistical results, and maintain databases while devising new data collection processes.

Statistics 52

Statistics Data mining Visualization Reporting 52

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 109

Data Lake Metadata Optimization Statistics 109

Sisense

OCTOBER 6, 2020

Let’s consider the differences between the two, and why they’re both important to the success of data-driven organizations. Digging into quantitative data. This is quantitative data. It’s “hard,” structured data that answers questions such as “how many?” Qualitative data benefits: Unlocking understanding.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

CIO Business Intelligence

MARCH 10, 2023

“The local team can be activated very quickly, ingest the data very quickly, and then create a statistical model and analytics model together with the business, sitting next to each other.

Forecasting 106

Forecasting Machine Learning Data Lake Digital Transformation 106

Cloudera

SEPTEMBER 15, 2022

Mark: The first element in the process is the link between the source data and the entry point into the data platform. At Ramsey International (RI), we refer to that layer in the architecture as the foundation, but others call it a staging area, raw zone, or even a source data lake.

Data Lake 79

Data Lake Data Architecture Data-driven Data Warehouse 79

Cloudera

DECEMBER 1, 2022

Mark: Freshness monitors the frequency of when the data resources are updated, which helps identify the most ideal data for decision making. In addition, freshness can help direct a focus toward stale data in an organization that can be pruned to reduce overall complexity. .

Metrics 82

Metrics Data Quality Data Lake Statistics 82

CIO Business Intelligence

JUNE 28, 2023

“We transferred our lab data—including safety, sensory efficacy, toxicology tests, product formulas, ingredients composition, and skin, scalp, and body diagnosis and treatment images—to our AWS data lake,” Gopalan says. This allowed us to derive insights more easily.”

Digital Transformation 105

Digital Transformation Cost-Benefit Informatics Data mining 105

AWS Big Data

FEBRUARY 6, 2023

Refactoring coupled compute and storage to a decoupling architecture is a modern data solution. It enables compute such as EMR instances and storage such as Amazon Simple Storage Service (Amazon S3) data lakes to scale. Jiseong Kim is a Senior Data Architect at AWS ProServe.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

BizAcuity

MAY 16, 2022

He went on to be the head brewer of Guinness and we thank him for not just great hand-crafted beers but subsequent research breakthroughs in statistical research as well. Data allowed Guinness to hold their market dominance for long. Data mining. That was in the 1900’s.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

AWS Big Data

MARCH 12, 2024

In recent years, data lakes have become a mainstream architecture, and data quality validation is a critical factor to improve the reusability and consistency of the data.

Data Quality 85

Data Quality Measurement Testing Visualization 85

Alation

APRIL 18, 2023

On the contrary, data profiling today describes an automated process, where a data user can “point and click” to return key results on a given asset, like aggregate functions, top patterns, outliers, inferred data types, and more. What do you learn about data through profiling? How do other thought leaders define it?

IT 52

IT Data Quality Metadata Data Governance 52

AWS Big Data

FEBRUARY 6, 2023

Based on the statistics of individual and aggregated application runs per queue and per user, you can determine the existing workload distribution by user. He has a specialty in big data services and technologies and an interest in building customer business outcomes together. Jiseong Kim is a Senior Data Architect at AWS ProServe.

Dashboards 72

Dashboards Optimization Data Lake Cost-Benefit 72

AWS Big Data

FEBRUARY 14, 2023

Organizations have chosen to build data lakes on top of Amazon Simple Storage Service (Amazon S3) for many years. A data lake is the most popular choice for organizations to store all their organizational data generated by different teams, across business domains, from all different formats, and even over history.

Data Lake 78

Data Lake Statistics Data Architecture Finance 78

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. It also helps you securely access your data in operational databases, data lakes, or third-party datasets with minimal movement or copying of data.

Testing 96

Testing Data Warehouse Metrics Cost-Benefit 96

AWS Big Data

JUNE 6, 2023

The purpose of this step is to understand our data quality statistics at the table level as well as at the ruleset level. Use the queries in this section to analyze your data quality metrics and create an Athena view to use to build a QuickSight dashboard in the next step.

Data Quality 68

Data Quality Metrics Visualization Dashboards 68

Sisense

JUNE 12, 2019

our annual client conference, I gave a presentation that took a deep dive into artificial intelligence and subgroups including AI, ML, and statistics. This includes such things as AI-powered data cleansing and modeling as well as general statistical analytics of the underlying data itself. Yesterday, during Eureka! ,

Analytics 75

Analytics Data-driven Dashboards IoT 75

erwin

JANUARY 11, 2019

The sad truth is that high-paid knowledge workers like data scientists spend up to 80 percent of their time finding and understanding source data and resolving errors or inconsistencies, rather than analyzing it for real value. Creating a High-Quality Data Pipeline.

Data Governance 40

Data Governance Risk Metadata Management 40

AWS Big Data

JULY 3, 2023

Terminology Let’s first discuss some of the terminology used in this post: Research data lake on Amazon S3 – A data lake is a large, centralized repository that allows you to manage all your structured and unstructured data at any scale. This is where the tagging feature in Apache Iceberg comes in handy.

Snapshot 80

Snapshot Data Lake Testing Strategy 80

AWS Big Data

NOVEMBER 29, 2023

Zero-ETL integration also enables you to load and analyze data from multiple operational database clusters in a new or existing Amazon Redshift instance to derive holistic insights across many applications. Use one click to access your data lake tables using auto-mounted AWS Glue data catalogs on Amazon Redshift for a simplified experience.

Data Warehouse 97

Data Warehouse Data Lake Analytics Machine Learning 97

Peter James Thomas

JUNE 20, 2019

Of course it can be argued that you can use statistics (and Google Trends in particular) to prove anything [1] , but I found the above figures striking. Feel free to substitute Data Lake for Data Warehouse if you want a more modern vibe, sadly it won’t change the failure statistics. . [5].

Cost-Benefit 55

Cost-Benefit Data Warehouse Consulting Data Science 55

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

AWS Big Data

NOVEMBER 8, 2023

Proposed Solution approach 2: Data Lake analytics The team used this approach with Redshift Spectrum to load only the required columns to Redshift Serverless, which avoided loading data into multiple yearly tables and directly to a single table. Create a data lake external schema and table in Redshift Serverless.

Data Lake 72

Data Lake Data Warehouse Cost-Benefit Optimization 72

Smart Data Collective

AUGUST 5, 2021

In this blog, we will cover an overview of Delta Lakes , its advantages, and how the above challenges can be overcome by moving to Delta Lake and migrating to Spark 3.0 What is Delta Lake? count, min/max values for columns) about the data in this file tags Map[String,String] Map containing metadata about this file.

Data Processing 143

Data Processing Metadata Broadcasting Statistics 143

CIO Business Intelligence

APRIL 4, 2023

Data warehouses, however, were not designed to support the demands of AI or semi-structured and unstructured data sources. Data lakes emerged to help solve complex data organizational challenges and store data in its natural format. Tolkien intimated, anything worth achieving takes time. Want to learn more?

Data Architecture 52

Data Architecture Data Lake Data Warehouse Cost-Benefit 52

DataKitchen

OCTOBER 11, 2021

Figure 2: Example data pipeline with DataOps automation. In this project, I automated data extraction from SFTP, the public websites, and the email attachments. The automated orchestration published the data to an AWS S3 Data Lake. Historic Balance – compares current data to previous or expected values.

Testing 157

Testing Metadata Dashboards Statistics 157

Alation

JULY 19, 2022

In this way, a data scientist benefits from business knowledge that they might not otherwise have access to. The catalog facilitates the synergy of the domain experts’ subject matter expertise with the data scientists statistical and coding expertise. Modern data catalogs surface a wide range of data asset types.

Metadata 59

Metadata Data Quality Statistics Data Science 59

CIO Business Intelligence

SEPTEMBER 22, 2023

What are the benefits of data management platforms? Modern, data-driven marketing teams must navigate a web of connected data sources and formats. All this data arrives by the terabyte, and a data management platform can help marketers make sense of it all. Of course, marketing also works.

Management 106

Management Advertising Data Lake Sales 106