AWS Big Data

DECEMBER 21, 2023

To create and manage the data products, smava uses Amazon Redshift , a cloud data warehouse. In this post, we show how smava optimized their data platform by using Amazon Redshift Serverless and Amazon Redshift data sharing to overcome right-sizing challenges for unpredictable workloads and further improve price-performance.

Data Lake 85

Data Lake Data Warehouse B2B Data-driven 85

DataKitchen

DECEMBER 9, 2022

By providing real-time visibility into the performance and behavior of data-related systems, DataOps observability enables organizations to identify and address issues before they become critical, and to optimize their data-related workflows for maximum efficiency and effectiveness.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

Jet Global

FEBRUARY 23, 2024

This field guide to data mapping will explore how data mapping connects volumes of data for enhanced decision-making. Why Data Mapping is Important Data mapping is a critical element of any data management initiative, such as data integration, data migration, data transformation, data warehousing, or automation.

Data Warehouse 52

Data Warehouse Reporting Data Transformation Sales 52

Smarten

AUGUST 4, 2023

Gartner predicts that, ‘data preparation will become a critical capability in more than 60% of data integration, analytics/BI, data science, data engineering and data lake enablement platforms.’

Data Lake 52

Data Lake Machine Learning Data Integration Optimization 52

AWS Big Data

APRIL 12, 2023

Amazon EMR on EKS provides a deployment option for Amazon EMR that allows organizations to run open-source big data frameworks on Amazon Elastic Kubernetes Service (Amazon EKS). This performance-optimized runtime offered by Amazon EMR makes your Spark jobs run fast and cost-effectively. As of the Amazon EMR 6.5 Amazon EMR 6.10

Testing 72

Testing Big Data Metadata Optimization 72

CIO Business Intelligence

FEBRUARY 16, 2023

But to augment its various businesses with ML and AI, Iyengar’s team first had to break down data silos within the organization and transform the company’s data operations. Digitizing was our first stake at the table in our data journey,” he says. The offensive side?

Unstructured Data 105

Unstructured Data Data Lake Prescriptive Analytics Digital Transformation 105

AWS Big Data

MAY 3, 2023

In this post, we provide a detailed overview of streaming messages with Amazon Managed Streaming for Apache Kafka (Amazon MSK) and Amazon ElastiCache for Redis , covering technical aspects and design considerations that are essential for achieving optimal results. We also discuss the key features, considerations, and design of the solution.

IoT 102

IoT Internet of Things Data Transformation Management 102

AWS Big Data

APRIL 27, 2023

It supports modern analytical data lake operations such as create table as select (CTAS), upsert and merge, and time travel queries. Athena also supports the ability to create views and perform VACUUM (snapshot expiration) on Apache Iceberg tables to optimize storage and performance. You can perform bulk load using a CTAS statement.

Data Lake 70

Data Lake Snapshot Optimization Data Transformation 70

AWS Big Data

JULY 20, 2023

Specifically, the system uses Amazon SageMaker Processing jobs to process the data stored in the data lake, employing the AWS SDK for Pandas (previously known as AWS Wrangler) for various data transformation operations, including cleaning, normalization, and feature engineering. Orca addressed this in several ways.

Data Lake 84

Data Lake Analytics Snapshot Optimization 84

AWS Big Data

AUGUST 1, 2023

AWS Glue is a serverless data discovery, load, and transformation service that will prepare data for consumption in BI and AI/ML activities. Solution overview This solution uses Amazon AppFlow to retrieve data from the Jira Cloud. Parquet is a columnar format to optimize subsequent querying. Choose Update.

Data Lake 81

Data Lake Data Transformation Cost-Benefit Data-driven 81

BizAcuity

APRIL 1, 2023

Techniques to large data handling Power BI uses import models that are loaded with data, which is then compressed and optimized and then stored to disk. When source data is loaded into memory, it is possible to see 10x compression, and so it is reasonable to expect that 10 GB of source data can compress to about 1 GB in size.

Optimization 52

Optimization Dashboards Modeling Sales 52

AWS Big Data

FEBRUARY 6, 2023

Additionally, a TCO calculator generates the TCO estimation of an optimized EMR cluster for facilitating the migration. For optimizing EMR cluster cost effectiveness, the following table provides general guidelines of choosing the proper type of EMR cluster and Amazon Elastic Compute Cloud (Amazon EC2) family.

Dashboards 72

Dashboards Optimization Data Lake Cost-Benefit 72

AWS Big Data

MAY 9, 2023

For workloads such as data transforms, joins, and queries, you can use G.1X With exponentially growing data sources and data lakes, customers want to run more data integration workloads, including their most demanding transforms, aggregations, joins, and queries. 1X (1 DPU) and G.2X DPU-hour ($) G.2X

Data Lake 84

Data Lake Cost-Benefit Data Integration Data Transformation 84

AWS Big Data

NOVEMBER 16, 2023

Data Vault 2.0 allows for the following: Agile data warehouse development Parallel data ingestion A scalable approach to handle multiple data sources even on the same entity A high level of automation Historization Full lineage support However, Data Vault 2.0

Enterprise 81

Enterprise Data Warehouse Data Lake Optimization 81

Cloudera

JULY 21, 2022

Cloudera Data Warehouse). Efficient batch data processing. Complex data transformations. Support for data rollup and summarization. Highly optimized time series queries. This reduces the total cost of ownership and frees internal resources for higher priority tasks than Druid maintenance and optimization.

Metrics 84

Metrics Slice and Dice Data Warehouse Dashboards 84

CIO Business Intelligence

JULY 5, 2022

What is the difference between business analytics and data analytics? Business analytics is a subset of data analytics. Data analytics is used across disciplines to find trends and solve problems using data mining , data cleansing, data transformation, data modeling, and more.

Business Analytics 132

Business Analytics Prescriptive Analytics Data mining Diagnostic Analytics 132

Cloudera

OCTOBER 13, 2020

Data Warehouse – in addition to a number of performance optimizations, DW has added a number of new features for better scalability, monitoring and reliability to enable self-service access with security and performance . Predict – Data Engineering (Apache Spark). New Services. Learn More, Keep in Touch.

Data Warehouse 93

Data Warehouse Machine Learning Visualization Data Lake 93

Ontotext

MARCH 20, 2024

The Bridge to Unified Data and Growth Imagine a world where your sales and marketing teams can effortlessly access and utilize data from various sources – LinkedIn, ZoomInfo, DBpedia, Yahoo Finance, and even your internal data sources – all within the familiar interface of Salesforce.

Data-driven 52

Data-driven Strategy Sales Data Integration 52

BizAcuity

SEPTEMBER 21, 2022

Power BI uses import models that are loaded with data, which is then compressed and optimized and then stored to disk. When source data is loaded into memory, it is possible to see 10x compression, and so it is reasonable to expect that 10 GB of source data can compress to about 1 GB in size.

Optimization 52

Optimization Dashboards Modeling Sales 52

Ontotext

MARCH 27, 2024

It accelerates data projects with data quality and lineage and contextualizes through ontologies , taxonomies, and vocabularies, making integrations easier. RDF is used extensively for data publishing and data interchange and is based on W3C and other industry standards. Increasingly, organizations are using both.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

AWS Big Data

APRIL 2, 2024

With these settings, you can now seamlessly ingest decompressed CloudWatch log data into Splunk using Firehose. This enables you to run high-performance, cost-efficient analytics on streaming data in Amazon S3 using services such as Amazon Athena , Amazon EMR , Amazon Redshift Spectrum , and Amazon QuickSight.

Metadata 82

Metadata Marketing Analytics Data Transformation 82

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 99

Data Lake Management Metrics Data Warehouse 99

AWS Big Data

MARCH 15, 2023

Infomedia was looking to build a cloud-based data platform to take advantage of highly scalable data storage with flexible and cloud-native processing tools to ingest, transform, and deliver datasets to their SaaS applications. The raw input data is stored in Amazon S3 in JSON format (called the bronze dataset layer).

Cost-Benefit 64

Cost-Benefit Data Processing Optimization Data-driven 64

CIO Business Intelligence

JANUARY 24, 2024

At Vanguard, “data and analytics enable us to fulfill on our mission to provide investors with the best chance for investment success by enabling us to glean actionable insights to drive personalized client experiences, scale advice, optimize investment and business operations, and reduce risk,” Swann says.

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

IBM Big Data Hub

JULY 28, 2023

Since its launch in 2020, DATA ONE has been successfully adopted by multinational companies across sectors, including insurance and banking, automotive, energy and utilities, manufacturing, logistics and telco. DATA ONE consists of three modules that can be activated as needed: Data Mover , a secure file-transfer enterprise solution.

Data Integration 59

Data Integration Optimization Software Insurance 59

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 66

Reporting Metrics Optimization Data Lake 66

FineReport

MARCH 31, 2024

Furthermore, these tools boast customization options, allowing users to tailor data sources to address areas critical to their business success, thereby generating actionable insights and customizable reports. Best BI Tools for Data Analysts 3.1 Key Features: Extensive library of pre-built connectors for diverse data sources.

Dashboards 52

Dashboards Visualization Data mining Data-driven 52

bridgei2i

NOVEMBER 17, 2020

The Lean AI wave can be imagined as a 4 step process: AI use case discovery: Identify the current processes amenable to data and AI driven improvement, design the solution roadmap and proactively think through the potential failure modes of enterprise adoption.

Deep Learning 85

Deep Learning Manufacturing Optimization Data-driven 85

Cloudera

DECEMBER 21, 2021

Since the release of Cloudera Data Engineering (CDE) more than a year ago , our number one goal was operationalizing Spark pipelines at scale with first class tooling designed to streamline automation and observability. This enabled new use-cases with customers that were using a mix of Spark and Hive to perform data transformations. .

Snapshot 117

Snapshot Data-driven Optimization Management 117

Octopai

JANUARY 19, 2021

With Octopai’s support and analysis of Azure Data Factory, enterprises can now view complete end-to-end data lineage from Azure Data Factory all the way through to reporting for the first time ever. About Octopai: Octopai was founded in 2015 by BI professionals who realized the need for dynamic solutions in a stagnant market.

Metadata 52

Metadata ROI Optimization Data Quality 52

Sisense

OCTOBER 15, 2020

Let’s look at a few ways that different industries take advantage of streaming data. How industries can benefit from streaming data. Automotive: Monitoring connected, autonomous cars in real time to optimize routes to avoid traffic and for diagnosis of mechanical issues. Optimizing object storage.

Dashboards 98

Dashboards IoT Optimization Internet of Things 98

datapine

SEPTEMBER 29, 2022

This means there are no unintended data errors, and it corresponds to its appropriate designation (e.g., Here, it all comes down to the data transformation error rate. In other words, it measures the time between when data is expected and the moment when it is readily available for use. date, month, and year).

Data Quality 241

Data Quality Metrics Data-driven Management 241

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

Jet Global

AUGUST 24, 2023

Optimized Resource Allocation: Finance teams can strategically allocate resources in a hybrid ERP environment. This optimization leads to improved efficiency, reduced operational costs, and better resource utilization. Cost Optimization: The hybrid model allows finance teams to balance their expenses effectively.

Finance 52

Finance Reporting Data Integration Risk 52

AWS Big Data

FEBRUARY 6, 2023

When migrating Hadoop workloads to Amazon EMR , it’s often difficult to identify the optimal cluster configuration without analyzing existing workloads by hand. It enables compute such as EMR instances and storage such as Amazon Simple Storage Service (Amazon S3) data lakes to scale. For more information, see the GitHub repo.

Cost-Benefit 52

Cost-Benefit Data Lake Dashboards Big Data 52

AWS Big Data

SEPTEMBER 19, 2023

We choose AWS Glue mainly due to its serverless nature, which simplifies infrastructure management with automatic provisioning and worker management, and the ability to perform complex data transformations at scale. With data democratization, many users lacked the knowledge to right-size their AWS Glue jobs.

Analytics 75

Analytics Risk Big Data Machine Learning 75

AWS Big Data

NOVEMBER 13, 2023

Amazon Redshift enables you to use SQL to analyze structured and semi-structured data across data warehouses, operational databases, and data lakes, using AWS-designed hardware and machine learning (ML) to deliver the best price-performance at scale. Shashank Tewari is a Senior Technical Account Manager at AWS.

Data Warehouse 88

Data Warehouse Data Lake Analytics Data Science 88