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. This automated approach reduces the need for manual intervention and streamlines the data quality evaluation process.

Data Quality 75

Data Quality Metrics Data-driven Visualization 75

AWS Big Data

JANUARY 17, 2024

By preserving historical versions, data lake time travel provides benefits such as auditing and compliance, data recovery and rollback, reproducible analysis, and data exploration at different points in time. Another popular transaction data lake use case is incremental query.

Data Lake 94

Data Lake Snapshot Big Data Data-driven 94

AWS Big Data

JULY 31, 2023

AWS DMS enables us to capture deltas, including deletes from the source database, through the use of Change Data Capture (CDC) configuration. CDC in DMS enables us to capture deltas without writing code and without missing any changes, which is critical for the integrity of the data. Under Transforms , choose SQL Query.

Sales 52

Sales Data Warehouse Visualization Testing 52

AWS Big Data

MARCH 13, 2024

This method uses GZIP compression to optimize storage consumption and query performance. You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches. You can test this solution yourself using the AWS Samples GitHub repository.

Analytics 95

Analytics IoT Metadata Internet of Things 95

AWS Big Data

JANUARY 27, 2023

Kinesis Data Firehose uses Lambda to perform data transformation and compression, storing the file in a compressed columnar format (Parquet) in the target S3 bucket. The AWS Glue Data Catalog has the table definitions for the data sources. To optimize query performance, we use Athena partition projections.

Analytics 61

Analytics Reporting Dashboards Visualization 61

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

IBM Big Data Hub

OCTOBER 16, 2023

AI governance refers to the practice of directing, managing and monitoring an organization’s AI activities. It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits.

Risk 71

Risk Modeling Management Metadata 71

AWS Big Data

OCTOBER 12, 2023

With EMR Serverless, you don’t have to configure, optimize, secure, or operate clusters to run applications with these frameworks. You can run analytics workloads at any scale with automatic scaling that resizes resources in seconds to meet changing data volumes and processing requirements. Do you have follow-up questions or feedback?

Big Data 107

Big Data Data-driven Management Visualization 107

Sisense

MARCH 14, 2021

Looking at the diagram, we see that Business Intelligence (BI) is a collection of analytical methods applied to big data to surface actionable intelligence by identifying patterns in voluminous data. As we move from right to left in the diagram, from big data to BI, we notice that unstructured data transforms into structured data.

Big Data 52

Big Data IoT Data Warehouse Data-driven 52

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

NOVEMBER 15, 2023

BMW Group uses 4,500 AWS Cloud accounts across the entire organization but is faced with the challenge of reducing unnecessary costs, optimizing spend, and having a central place to monitor costs. For more information on this foundation, refer to A Detailed Overview of the Cost Intelligence Dashboard.

Dashboards 96

Dashboards Analytics Metadata Data Warehouse 96

CIO Business Intelligence

DECEMBER 6, 2023

Notably, a partner with global reach can be particularly valuable to an organisation with operations with a global presence; since the structure of most multinational organisations is optimised to support their core business rather than initiatives like digital transformation.

Digital Transformation 113

Digital Transformation Software Cost-Benefit Manufacturing 113

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 85

Enterprise Data Warehouse Data Lake Optimization 85

AWS Big Data

OCTOBER 11, 2023

Under the Transparency in Coverage (TCR) rule , hospitals and payors to publish their pricing data in a machine-readable format. For more information, refer to Delivering Consumer-friendly Healthcare Transparency in Coverage On AWS. The Data Catalog now contains references to the machine-readable data.

Visualization 97

Visualization Dashboards Data-driven Gap analysis 97

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 104

IoT Internet of Things Data Transformation Management 104

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.

Data Lake 74

Data Lake Snapshot Optimization Data Transformation 74

O'Reilly on Data

OCTOBER 19, 2021

but to reference concrete tooling used today in order to ground what could otherwise be a somewhat abstract exercise. Adapted from the book Effective Data Science Infrastructure. However, none of these layers help with modeling and optimization. Let’s now take a tour of the various layers, to begin to map the territory.

IT 347

IT Testing Experimentation Software 347

CIO Business Intelligence

JUNE 29, 2022

If you can’t make sense of your business data, you’re effectively flying blind. Insights hidden in your data are essential for optimizing business operations, finetuning your customer experience, and developing new products — or new lines of business, like predictive maintenance. Azure Data Factory.

Data Lake 113

Data Lake Analytics Data Warehouse Machine Learning 113

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 92

Data Warehouse Data Lake Analytics Data Science 92

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

SEPTEMBER 6, 2023

Stored procedures are commonly used to encapsulate logic for data transformation, data validation, and business-specific logic. You can also schedule stored procedures to automate data processing on Amazon Redshift. For more information, refer to Bringing your stored procedures to Amazon Redshift.

Data Warehouse 96

Data Warehouse Insurance Statistics Software 96

AWS Big Data

JULY 25, 2023

For more information on how to connect to a database, refer to tDBConnection. The output component defines that the data being processed in the job’s workflow will land in Redshift Serverless. All configuration for ingestion or replicating data from your desired sources to Redshift Serverless is done in a single input screen.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

AWS Big Data

OCTOBER 31, 2023

Customers rely on data from different sources such as mobile applications, clickstream events from websites, historical data, and more to deduce meaningful patterns to optimize their products, services, and processes. citibike-tripdata-destination-ACCOUNT_ID – The bucket used for storing the transformed dataset.

Data Processing 90

Data Processing Management Publishing Testing 90

Ontotext

AUGUST 24, 2023

To deal with this issue, GraphDB implements a smart Graph Replace optimization that helps you calculate the internal data and only shows you the newly added and removed statements. The second approach is to use some Data Integration Platform. Ideally, the data in the data source should come with persistent identifiers.

Data Integration 52

Data Integration Modeling Business Objectives Optimization 52

FineReport

APRIL 21, 2024

In summary, embedded analytics refers to actionable intelligence seamlessly integrated into customer-facing products, applications, or services. However, users note limitations in advanced analytics, customization, data transformation challenges, and issues with offline access and slow loading times for large datasets.

Dashboards 52

Dashboards Visualization Interactive Business Intelligence 52

Alation

OCTOBER 28, 2021

It defines how data can be collected and used within an organization, and empowers data teams to: Maintain compliance, even as laws change. Uncover intelligence from data. Protect data at the source. Put data into action to optimize the patient experience and adapt to changing business models.

Data Governance 52

Data Governance Measurement Metrics Data Quality 52

AWS Big Data

MARCH 3, 2023

Data ingestion – Steps 1 and 2 use AWS DMS, which connects to the source database and moves full and incremental data (CDC) to Amazon S3 in Parquet format. Let’s refer to this S3 bucket as the raw layer. Data transformation – Steps 3 and 4 represent an EMR Serverless Spark application (Amazon EMR 6.9

Data Lake 84

Data Lake Dashboards Metrics Metadata 84

AWS Big Data

MAY 9, 2023

AWS Glue Studio is a graphical interface that makes it easy to create, run, and monitor extract, transform, and load (ETL) jobs in AWS Glue. It allows you to visually compose data transformation workflows using nodes that represent different data handling steps, which later are converted automatically into code to run.

Visualization 75

Visualization Marketing Big Data IT 75

Sisense

MAY 11, 2021

With our strategy in mind, we factored in our consumers and consuming services, which primarily are Sisense Fusion Analytics and Cloud Data Teams. Interestingly, this ad hoc analysis benefits from a single source of truth that is easy to query to allow for quickly querying of raw data alongside the cleanest data (i.e.,

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Occam's Razor

OCTOBER 19, 2010

so you have some reference as to where each item fits (and this will also make it easier for you to pick tools for the priority order referenced in Context #3 above). A huge vast majority of clicks coming from search engines continue to be organic clicks (which is why I love and adore search engine optimization). Not a single one.

Analytics 135

Analytics Testing Measurement Optimization 135

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 103

Data Lake Management Metrics Data Warehouse 103

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 67

Cost-Benefit Data Processing Optimization Data-driven 67

Smarten

JANUARY 4, 2018

Extract, Transform and Load (ETL) refers to a process of connecting to data sources, integrating data from various data sources, improving data quality, aggregating it and then storing it in staging data source or data marts or data warehouses for consumption of various business applications including BI, Analytics and Reporting.

Data Warehouse 40

Data Warehouse OLAP Data Governance Optimization 40

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. For full instructions, refer to Jira Cloud connector for Amazon AppFlow.

Data Lake 86

Data Lake Data Transformation Cost-Benefit Data-driven 86

CIO Business Intelligence

JANUARY 24, 2024

Agent Swarms offer a strategic solution: they can autonomously oversee repetitive, rules-based, high-volume tasks, optimizing back-office functions and ensuring regulatory compliance with precision. Identify patterns in customer behavior, predict market trends, optimize inventory management, or flag inefficiencies in operations.

IoT 109

IoT Machine Learning Optimization Internet of Things 109

Jet Global

MAY 28, 2019

Databases can be stored either on a local server or in the cloud and can be access for reporting in many different ways, through limited native tools included with the system collecting the data itself, to Excel exports or various direct connectivity options. Enter the Warehouse.

Data Warehouse 85

Data Warehouse Reporting Business Intelligence Sales 85