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. The ultimate goal is to raise awareness of cloud efficiency and optimize cloud utilization in a cost-effective and sustainable manner.

Dashboards 107

Dashboards Analytics Metadata Data Warehouse 107

datapine

SEPTEMBER 29, 2022

This person (or group of individuals) ensures that the theory behind data quality is communicated to the development team. 2 – Data profiling. Data profiling is an essential process in the DQM lifecycle. This means there are no unintended data errors, and it corresponds to its appropriate designation (e.g.,

Data Quality 241

Data Quality Metrics Data-driven Management 241

AWS Big Data

APRIL 25, 2024

Data lakes provide a centralized repository for data from various sources, enabling organizations to unlock valuable insights and drive data-driven decision-making. However, as data volumes continue to grow, optimizing data layout and organization becomes crucial for efficient querying and analysis.

Optimization 72

Optimization Data Lake Cost-Benefit Reporting 72

CIO Business Intelligence

AUGUST 3, 2023

It also used device data to develop Lenovo Device Intelligence, which uses AI-driven predictive analytics to help customers understand and proactively prevent and solve potential IT issues. Lenovo Device Intelligence can also help to optimize IT support costs, reduce employee downtime, and improve the user experience, the company says.

Analytics 98

Analytics Data Lake Metadata Cost-Benefit 98

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 86

Testing Big Data Metadata Optimization 86

AWS Big Data

APRIL 2, 2024

You can see the decompressed data has metadata information such as logGroup , logStream , and subscriptionFilters , and the actual data is included within the message field under logEvents (the following example shows an example of CloudTrail events in the CloudWatch Logs).

Metadata 99

Metadata Marketing Analytics Data Transformation 99

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 104

Data Lake Data Warehouse Data-driven B2B 104

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 94

Data Lake Analytics Snapshot Data Quality 94

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 98

Enterprise Data Warehouse Data Lake Optimization 98

Cloudera

OCTOBER 11, 2021

The platform converges data cataloging, data ingestion, data profiling, data tagging, data discovery, and data exploration into a unified platform, driven by metadata. Modak Nabu automates repetitive tasks in the data preparation process and thus accelerates the data preparation by 4x.

Data Lake 95

Data Lake Cost-Benefit Data-driven Dashboards 95

Octopai

JANUARY 19, 2021

This is done by visualizing the Azure Data Factory pipelines’ full column-level with source-to-target traceability through different data transformations at the most detailed level. Octopai can fully map the BI landscape and trace metadata movement in a mixed environment including complex multi-vendor landscapes.

Metadata 52

Metadata ROI Machine Learning Data Quality 52

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 117

Data Lake Management Metrics Data Warehouse 117

Alation

APRIL 4, 2023

Now, joint users will get an enhanced view into cloud and data transformations , with valuable context to guide smarter usage. Integrating helpful metadata into user workflows gives all people, from data scientists to analysts , the context they need to use data more effectively.

Metadata 52

Metadata Cost-Benefit Data Transformation Predictive Modeling 52

IBM Big Data Hub

JULY 5, 2023

The challenges of a monolithic data lake architecture Data lakes are, at a high level, single repositories of data at scale. Data may be stored in its raw original form or optimized into a different format suitable for consumption by specialized engines.

Data Lake 60

Data Lake Metadata Cost-Benefit Data Warehouse 60

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 92

Data Lake Data Transformation Data-driven Cost-Benefit 92

IBM Big Data Hub

MARCH 14, 2024

This involves unifying and sharing a single copy of data and metadata across IBM® watsonx.data ™, IBM® Db2 ®, IBM® Db2® Warehouse and IBM® Netezza ®, using native integrations and supporting open formats, all without the need for migration or recataloging. With Netezza support for 1.2

Cost-Benefit 75

Cost-Benefit Metadata Optimization Management 75

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 73

Cost-Benefit Data Processing Optimization Data-driven 73

AWS Big Data

MARCH 9, 2023

Additionally, there are major rewrites to deliver developer-focused improvements, including static type checking, enhanced runtime validation, strong consistency in call patterns, and optimized event chaining. The following eventNames and eventCodes are returned as part of the onChange callback when there is a change in the SDK code status.

Slice and Dice 88

Slice and Dice Dashboards Analytics Interactive 88

IBM Big Data Hub

OCTOBER 16, 2023

It includes processes that trace and document the origin of data, models and associated metadata and pipelines for audits. It also lets you choose the right engine for the right workload at the right cost, potentially reducing your data warehouse costs by optimizing workloads. Track models and drive transparent processes.

Risk 70

Risk Modeling Management Metadata 70

AWS Big Data

OCTOBER 11, 2023

Due to this low complexity, the solution uses AWS serverless services to ingest the data, transform it, and make it available for analytics. The serverless architecture features auto scaling, high availability, and a pay-as-you-go billing model to increase agility and optimize costs.

Visualization 111

Visualization Dashboards Data-driven Gap analysis 111

Cloudera

NOVEMBER 22, 2021

In addition, more data is becoming available for processing / enrichment of existing and new use cases e.g., recently we have experienced a rapid growth in data collection at the edge and an increase in availability of frameworks for processing that data. As a result, alternative data integration technologies (e.g.,

Data Processing 94

Data Processing Data Warehouse Enterprise Visualization 94

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. Choose Run.

Analytics 110

Analytics IoT Metadata Internet of Things 110

Octopai

AUGUST 11, 2024

By reverse-engineering, parsing, and converting scripts, Octopai seamlessly connects all data points within and across organizational systems. While open-source tools such as Apache Atlas, Open Metadata, Egeria, Spline, and OpenLineage offer valuable capabilities, they come with their own sets of pros and cons.

Metadata 40

Metadata Visualization Data Quality Data Governance 40

Octopai

JUNE 9, 2024

By doing so, they aimed to drive innovation, optimize operations, and enhance patient care. They invested heavily in data infrastructure and hired a talented team of data scientists and analysts. Predictive analytics models became more accurate as they were based on trustworthy data flows. This is where Octopai excels.

IT 52

IT Data-driven Predictive Analytics Data Strategy 52

IBM Big Data Hub

JULY 17, 2023

.” Sean Im, CEO, Samsung SDS America “In the field of generative AI and foundation models, watsonx is a platform that will enable us to meet our customers’ requirements in terms of optimization and security, while allowing them to benefit from the dynamism and innovations of the open-source community.”

Machine Learning 62

Machine Learning Data Warehouse Modeling Cost-Benefit 62

Ontotext

MARCH 27, 2024

For example, GPS, social media, cell phone handoffs are modeled as graphs while data catalogs, data lineage and MDM tools leverage knowledge graphs for linking metadata with semantics. RDF is used extensively for data publishing and data interchange and is based on W3C and other industry standards.

Modeling 53

Modeling Metadata Data Quality Enterprise 53

Cloudera

MARCH 14, 2023

A critical feature for every developer however is to get instantaneous feedback like configuration validations or performance metrics, as well as previewing data transformations for each step of their data flow. Attributes contain key metadata like the source directory of a file or the source topic of a Kafka message.

Testing 84

Testing Publishing Metadata Interactive 84

Alation

NOVEMBER 22, 2022

Before you implement a data governance framework, you need to know the data you already have. This means you need to: Inventory data: Know all information resources and relevant metadata. Classify data: Organize structured and unstructured data into relevant categories. Reuse metadata productively.

Data Governance 52

Data Governance Metadata Data-driven Unstructured Data 52

AWS Big Data

JANUARY 17, 2024

Incremental query refers to a query strategy that focuses on processing and analyzing only the new or updated data within a data lake since the last query. The key idea behind incremental queries is to use metadata or change tracking mechanisms to identify the new or modified data since the last query.

Data Lake 107

Data Lake Snapshot Big Data Data-driven 107

IBM Big Data Hub

JANUARY 18, 2023

A read-optimized platform that can integrate data from multiple applications emerged. In another decade, the internet and mobile started the generate data of unforeseen volume, variety and velocity. This adds an additional ETL step, making the data even more stale. Data lakehouse was created to solve these problems.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 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. Data transformation – Steps 3 and 4 represent an EMR Serverless Spark application (Amazon EMR 6.9 Let’s refer to this S3 bucket as the raw layer.

Data Lake 91

Data Lake Dashboards Metrics Metadata 91

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 Visualization 52

Jet Global

MAY 1, 2023

Reports In formats that are both static and interactive, these showcase tabular views of data. Strategic Objective Provide an optimal user experience regardless of where and how users prefer to access information. Ideally, your primary data source should belong in this group. addresses). Build your first set of reports.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

Jet Global

JULY 19, 2023

Hide Pickers provides an option to hide visual pickers to optimize space and remove redundant information. Context Menu for Non-Grouped Data provides further self-service user empowerment with our new context menu for ungrouped data. Simba Partnership now offers two new options for data connectors.

Dashboards 52

Dashboards Visualization Reporting Interactive 52

AWS Big Data

FEBRUARY 18, 2025

To optimize their security operations, organizations are adopting modern approaches that combine real-time monitoring with scalable data analytics. They are using data lake architectures and Apache Iceberg to efficiently process large volumes of security data while minimizing operational overhead.

Snapshot 76

Snapshot Optimization Data Lake Metadata 76

BI-Survey

MARCH 6, 2025

While efficiency is a priority, data quality and security remain non-negotiable. Developing and maintaining data transformation pipelines are among the first tasks to be targeted for automation. However, caution is advised since accuracy, timeliness, and other aspects of data quality depend on the quality of data pipelines.

Data Warehouse 52

Data Warehouse Metadata Unstructured Data Data-driven 52

AWS Big Data

DECEMBER 2, 2024

AWS Glue establishes a secure connection to HubSpot using OAuth for authorization and TLS for data encryption in transit. AWS Glue also supports the ability to apply complex data transformations, enabling efficient data integration and preparation to meet your needs.

Data Lake 89

Data Lake Testing Data Integration Metadata 89