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. The following is a visual representation of an example job where the number of workers is 10. workerUtilization showed 1.0 100%) based on the workload requirements.

Metrics 97

Metrics Data Lake Cost-Benefit Dashboards 97

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 80

Data Science Data Analytics Prescriptive Analytics Analytics 80

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. Visual IDE for data pipelines; RPA for rote tasks.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

AWS Big Data

JUNE 6, 2023

We are excited to announce the General Availability of AWS Glue Data Quality. Our journey started by working backward from our customers who create, manage, and operate data lakes and data warehouses for analytics and machine learning. This reduces manual data analysis and rule identification efforts from days to hours.

Data Quality 96

Data Quality Statistics Data Lake Visualization 96

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 103

Data Warehouse Data Lake Analytics Machine Learning 103

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

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

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. On the AWS Glue console, under ETL jobs in the navigation pane, choose Visual ETL. In the Create job section, choose Visual ETL.x

Data Quality 92

Data Quality Measurement Testing Visualization 92

Sisense

DECEMBER 11, 2019

Scott whisked us through the history of business intelligence from its first definition in 1958 to the current rise of Big Data. Scott outlined how this change has driven a shift in the role of data teams , who now occupy strategic business positions. Diving deeper into the datasphere: Data lakes — best practices.

Data Lake 80

Data Lake Big Data Sales Data-driven 80

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. Data mining allows refining and analyzing of the data on a near-real time basis.

Business Intelligence 52

Business Intelligence Data mining Visualization Data Lake 52

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?” The challenge comes when the data becomes huge and fast-changing.

Statistics 98

Statistics Unstructured Data Data-driven Visualization 98

AWS Big Data

FEBRUARY 6, 2023

In this post, we dive deep into the tool, walking through all steps from log ingestion, transformation, visualization, and architecture design to calculate TCO. With QuickSight, you can visualize YARN log data and conduct analysis against the datasets generated by pre-built dashboard templates and a widget.

Dashboards 78

Dashboards Optimization Data Lake Cost-Benefit 78

AWS Big Data

MAY 23, 2024

Solution overview Let’s consider an example data quality pipeline where a data engineer ingests data from a raw zone and loads it into a curated zone in a data lake. To learn more about job bookmarks, refer to Tracking processed data using job bookmarks. Navigate to the Job details tab to configure the job.

Data Quality 88

Data Quality Metrics Data Lake Sales 88

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. Living in a World of Big Data. It all starts with the data. Data literacy and data skills, which created the forgotten dark data lakes in the first place, are still scarce.

Analytics 75

Analytics Data-driven Dashboards IoT 75

Domino Data Lab

AUGUST 8, 2019

He’s been out of Wolfram for a while and writing exquisite science books including Elements: A Visual Explanation of Every Known Atom in the Universe and Molecules: The Architecture of Everything. Historically, grad students in physics and physical sciences have been excellent candidates for data science teams.

Data Science 71

Data Science Machine Learning Data Governance Statistics 71

Andrew White

JANUARY 11, 2021

As such any Data and Analytics strategy needs to incorporate data sovereignty as per of its D&A governance program. Coding skills – SQL, Python or application familiarity – ETL & visualization? Does Data warehouse as a software tool will play role in future of Data & Analytics strategy?

Data Analytics 52

Data Analytics Analytics Data-driven Finance 52