AWS Big Data

MAY 25, 2023

Data transformation plays a pivotal role in providing the necessary data insights for businesses in any organization, small and large. To gain these insights, customers often perform ETL (extract, transform, and load) jobs from their source systems and output an enriched dataset.

Reporting 70

Reporting Metrics Optimization Data Lake 70

AWS Big Data

JUNE 6, 2023

Furthermore, it allows for necessary actions to be taken, such as rectifying errors in the data source, refining data transformation processes, and updating data quality rules. The Lambda function is responsible for converting the data quality metrics and dispatching them to the designated email addresses via Amazon SNS.

Data Quality 75

Data Quality Metrics Data-driven Visualization 75

AWS Big Data

FEBRUARY 6, 2023

Let’s look at some key metrics. After analyzing YARN logs by various metrics, you’re ready to design future EMR architectures. He helps customers innovate their business with AWS Analytics, IoT, and AI/ML services. Jiseong Kim is a Senior Data Architect at AWS ProServe.

Dashboards 77

Dashboards Optimization Data Lake Cost-Benefit 77

AWS Big Data

APRIL 11, 2023

In this post, we discuss how to streamline inventory management forecasting systems with AWS managed analytics, AI/ML, and database services. With the proliferation of IoT devices and the abundance of data generated by them, it has become possible to collect real-time data on inventory levels, customer behavior, and other key metrics.

Forecasting 77

Forecasting Management IoT Data-driven 77

DataKitchen

OCTOBER 5, 2021

A DataOps Engineer owns the assembly line that’s used to build a data and analytic product. That’s the state of data analytics today. . Figure 2: Data operations can be conceptualized as a series of automated factory assembly lines. Where are the data engineers, scientists and analytics?

Testing 152

Testing Dashboards Measurement Experimentation 152

AWS Big Data

OCTOBER 11, 2023

Organizations with legacy, on-premises, near-real-time analytics solutions typically rely on self-managed relational databases as their data store for analytics workloads. Near-real-time streaming analytics captures the value of operational data and metrics to provide new insights to create business opportunities.

Management 106

Management Metadata Analytics Dashboards 106

AWS Big Data

FEBRUARY 6, 2023

Use case overview Migrating Hadoop workloads to Amazon EMR accelerates big data analytics modernization, increases productivity, and reduces operational cost. Refactoring coupled compute and storage to a decoupling architecture is a modern data solution. Jiseong Kim is a Senior Data Architect at AWS ProServe.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

AWS Big Data

FEBRUARY 26, 2024

In cases where your application demands supplementary query features, such as conducting full-text searches on the data stored in a table, you may explore the utilization of alternative services like Amazon OpenSearch Service to meet these particular needs. Monitoring You can use Amazon CloudWatch to monitor the pipeline metrics.

Dashboards 63

Dashboards Testing Metrics Optimization 63

Cloudera

MARCH 14, 2023

Key requirements for building data pipelines Every data pipeline starts with a business requirement. For example, a developer may be asked to tap into the data of a newly acquired application, parsing and transforming it before delivering it to the business’s favorite analytical system where it can be joined with existing data sets.

Testing 87

Testing Publishing Metadata Interactive 87

AWS Big Data

MAY 16, 2023

In this series of posts, we walk you through how we use Amazon QuickSight , a serverless, fully managed, business intelligence (BI) service that enables data-driven decision making at scale. Solution overview The following highly simplified architectural diagram illustrates the smart sensor data collection and processing.

Dashboards 79

Dashboards Statistics Data Collection Business Intelligence 79

AWS Big Data

NOVEMBER 15, 2023

BMW Cloud Efficiency Analytics (CLEA) is a homegrown tool developed within the BMW FinOps CoE (Center of Excellence) aiming to optimize and reduce costs across all these accounts. In this post, we explore how the BMW Group FinOps CoE implemented their Cloud Efficiency Analytics tool (CLEA), powered by Amazon QuickSight and Amazon Athena.

Dashboards 96

Dashboards Analytics Metadata Data Warehouse 96

DataKitchen

JULY 27, 2023

Let’s go through the ten Azure data pipeline tools Azure Data Factory : This cloud-based data integration service allows you to create data-driven workflows for orchestrating and automating data movement and transformation. You can use it for big data analytics and machine learning workloads.

Machine Learning 130

Machine Learning Cost-Benefit Data Transformation Testing 130

DataRobot Blog

MARCH 10, 2022

The first step in building a model that can predict machine failure and even recommend the next best course of action is to aggregate, clean, and prepare data to train against. This task may require complex joins, aggregations, filtering, window functions, and many other data transformations against extremely large-scale data sets.

Manufacturing 52

Manufacturing IoT Machine Learning Forecasting 52

AWS Big Data

JULY 20, 2023

One key component that plays a central role in modern data architectures is the data lake, which allows organizations to store and analyze large amounts of data in a cost-effective manner and run advanced analytics and machine learning (ML) at scale. To overcome these issues, Orca decided to build a data lake.

Data Lake 89

Data Lake Analytics Snapshot Optimization 89

AWS Big Data

JUNE 20, 2023

Kinesis Data Firehose is a fully managed service for delivering near-real-time streaming data to various destinations for storage and performing near-real-time analytics. You can perform analytics on VPC flow logs delivered from your VPC using the Kinesis Data Firehose integration with Datadog as a destination.

Dashboards 86

Dashboards Visualization Metrics Data Transformation 86

Alation

OCTOBER 18, 2022

Alation is pleased to be named a dbt Metrics Partner and to announce the start of a partnership with dbt, which will bring dbt data into the Alation data catalog. In the modern data stack, dbt is a key tool to make data ready for analysis. Data Transformation in the Modern Data Stack.

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

CIO Business Intelligence

JUNE 23, 2022

If the data used to fuel AI/ML models is inaccurate, incomplete, or outdated, the models won’t deliver the desired outcomes. Data is the key raw material for analytics and decision-making. How might we improve the outcomes from our data supply chain? Recommended action plan: Create a map of your data supply chain.

Data Quality 98

Data Quality Key Performance Indicator Metrics KPI 98

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. Bindu Chandramohan, Lead, Data Analytics, Alation : Thanks, Jason!

Metrics 52

Metrics Dashboards Sales Reporting 52

Sisense

AUGUST 6, 2020

An obvious mechanical answer is: use relevance as a metric. Another important method is to benchmark existing metrics. Know the limitations of your existing dataset and answer these questions: What categories of data are there? What data transformations are needed from your data scientists to prepare the data?

Management 95

Management Machine Learning Key Performance Indicator Cost-Benefit 95

DataKitchen

OCTOBER 25, 2022

Its goal is to provide visibility of every journey that data takes from source to customer value across every tool, environment, data store, data and analytic team, and customer so that problems are detected, localized and raised immediately. A data journey spans and tracks multiple pipelines.

Testing 130

Testing Data-driven Visualization Dashboards 130

Occam's Razor

OCTOBER 19, 2010

What is the first thing you want when you think about web analytics? recommending tools for the complete web analytics 2.0 Disclosure:] I am the co-Founder of Market Motive Inc and the Analytics Evangelist for Google. Web Analytics 2.0. This blog post is about web analytics 2.0. Of course tools. Don't be.

Analytics 135

Analytics Testing Measurement Optimization 135

AWS Big Data

MARCH 3, 2023

You can then apply transformations and store data in Delta format for managing inserts, updates, and deletes. Amazon EMR Serverless is a serverless option in Amazon EMR that makes it easy for data analysts and engineers to run open-source big data analytics frameworks without configuring, managing, and scaling clusters or servers.

Data Lake 84

Data Lake Dashboards Metrics Metadata 84

Sisense

MAY 11, 2021

You can’t talk about data analytics without talking about data modeling. These two functions are nearly inseparable as we move further into a world of analytics that blends sources of varying volume, variety, veracity, and velocity. But this was only the tip of the analytics iceberg.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Alation

OCTOBER 28, 2021

Data & analytics represents a major opportunity to tackle these challenges. Indeed, many healthcare organizations today are embracing digital transformation and using data to enhance operations. To make good on this potential, healthcare organizations need to understand their data and how they can use it.

Data Governance 52

Data Governance Measurement Metrics Data Quality 52

Ontotext

DECEMBER 9, 2020

Maybe you spend an inordinate amount of time and effort managing operational concerns, deployments, monitoring, metrics and log collation? We all want to solve the interesting data challenges, build analytics, generate graph embeddings and train smart machine learning models over our knowledge graph data.

Modeling 130

Modeling Management Optimization Metrics 130

AWS Big Data

MARCH 3, 2023

It has been well published since the State of DevOps 2019 DORA Metrics were published that with DevOps, companies can deploy software 208 times more often and 106 times faster, recover from incidents 2,604 times faster, and release 7 times fewer defects. For users that require a unified view of software quality, this is unacceptable.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

FEBRUARY 21, 2023

We use Apache Spark as our main data processing engine and have over 1,000 Spark applications running over massive amounts of data every day. These Spark applications implement our business logic ranging from data transformation, machine learning (ML) model inference, to operational tasks. Their costs were climbing.

Cost-Benefit 55

Cost-Benefit Informatics Optimization Management 55

AWS Big Data

NOVEMBER 29, 2023

dbt is an open source, SQL-first templating engine that allows you to write repeatable and extensible data transforms in Python and SQL. dbt is predominantly used by data warehouses (such as Amazon Redshift ) customers who are looking to keep their data transform logic separate from storage and engine.

Data Lake 104

Data Lake Management Metrics Data Warehouse 104

DataKitchen

APRIL 26, 2021

In early April 2021, DataKItchen sat down with Jonathan Hodges, VP Data Management & Analytics, at Workiva ; Chuck Smith, VP of R&D Data Strategy at GlaxoSmithKline (GSK) ; and Chris Bergh, CEO and Head Chef at DataKitchen, to find out about their enterprise DataOps transformation journey, including key successes and lessons learned.

Measurement 246

Measurement Metrics Data-driven Testing 246

AWS Big Data

NOVEMBER 7, 2023

Second, organizations still need transformations like cleansing, deduplication, and combining datasets for analysis and machine learning (ML). For these, AWS Glue provides fast, scalable data transformation. Within seconds of new data coming into Amazon Aurora MySQL, the data is replicated to Amazon Redshift.

Dashboards 73

Dashboards Data-driven Data Integration Data Lake 73

CIO Business Intelligence

APRIL 30, 2024

At Tableau Conference 2024 in San Diego today, Tableau announced new AI features for Tableau Pulse and Einstein Copilot for Tableau, along with several platform improvements aimed at democratizing data insights. Tableau pitched its unveiling of Tableau Pulse last year as the harbinger of a new era of proactive analytics. Metric Goals.

Analytics 96

Analytics Metrics Visualization Dashboards 96

AWS Big Data

SEPTEMBER 19, 2023

To make high-quality decisions, we need to collect user event data from various sources and update risk profiles in real time. We also need to be able to add new fields and metrics to the risk profiles as our team identifies new attacks, without needing engineering intervention or complex deployments.

Analytics 80

Analytics Risk Big Data Machine Learning 80

AWS Big Data

DECEMBER 21, 2023

To speed up the self-service analytics and foster innovation based on data, a solution was needed to provide ways to allow any team to create data products on their own in a decentralized manner. To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse.

Data Lake 90

Data Lake Data Warehouse Data-driven B2B 90

Jet Global

MAY 28, 2019

High level, a data warehouse is a collection of business data from multiple sources used optimized for reporting, analytics and decision making. This automated process of extracting, transforming, and loading data into a data warehouse is commonly called ETL and it’s a huge advantage for analyzing your data.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85

Birst BI

FEBRUARY 25, 2020

Managing large-scale data warehouse systems has been known to be very administrative, costly, and lead to analytic silos. The good news is that Snowflake, the cloud data platform, lowers costs and administrative overhead. The result is a lower total cost of ownership and trusted data and analytics.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Architecture Enterprise 52

Alation

NOVEMBER 22, 2022

Effective data governance for the public sector enables entities to ensure data quality, enhance security, protect privacy, and meet compliance requirements. With so much focus on compliance, democratizing data for self-service analytics can present a challenge. Standardizing data formats. Securing Data.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

DataKitchen

JANUARY 23, 2023

On the other hand, DataOps Observability refers to understanding the state and behavior of data as it flows through systems. It allows organizations to see how data is being used, where it is coming from, and how it is being transformed. We must do the same as data analytic teams.

Testing 130

Testing Data Governance Data Quality Data-driven 130