DataKitchen

DECEMBER 20, 2020

The agile alliance definition of business agility consists of two parts. The DataOps Engineering skillset includes hybrid and cloud platforms, orchestration, data architecture, data integration, data transformation, CI/CD, real-time messaging, and containers. Companies that move slowly get left behind. .

Data-driven 147

Data-driven Manufacturing Data Architecture Data Analytics 147

AWS Big Data

DECEMBER 13, 2023

In addition to using native managed AWS services that BMS didn’t need to worry about upgrading, BMS was looking to offer an ETL service to non-technical business users that could visually compose data transformation workflows and seamlessly run them on the AWS Glue Apache Spark-based serverless data integration engine.

Metadata 84

Metadata Data Lake Visualization Data Transformation 84

DataKitchen

OCTOBER 5, 2021

The data organization wants to run the Value Pipeline as robustly as a six sigma factory, and it must be able to implement and deploy process improvements as rapidly as a Silicon Valley start-up. The data engineer builds data transformations. Their product is the data. When is a Task “Done”. They are “done,” right?

Testing 157

Testing Dashboards Measurement Experimentation 157

Anmut

MARCH 24, 2022

We could give many answers, but they all centre on the same root cause: most data leaders focus on flashy technology and symptomatic fixes instead of approaching data transformation in a way that addresses the root causes of data problems and leads to tangible results and business success. What is a data landscape?

ROI 52

ROI Measurement Data-driven Data Transformation 52

CIO Business Intelligence

JANUARY 24, 2024

With nearly 800 locations, RaceTrac handles a substantial volume of data, encompassing 260 million transactions annually, alongside data feeds from store cameras and internet of things (IoT) devices embedded in fuel pumps. This empowers data users to make decisions informed by data and in real-time with increased confidence.”

Data Strategy 136

Data Strategy Strategy Unstructured Data Data Governance 136

AWS Big Data

DECEMBER 5, 2023

A combination of Amazon Redshift Spectrum and COPY commands are used to ingest the survey data stored as CSV files. For the files with unknown structures, AWS Glue crawlers are used to extract metadata and create table definitions in the Data Catalog.

Measurement 78

Measurement Dashboards Data Warehouse Analytics 78

Jen Stirrup

SEPTEMBER 30, 2021

This initial phase focuses on understanding the business value-add from a business perspective, then translating this knowledge into a data mining problem definition. For example, data can be filtered so that the investigation can be focused more specifically.

Business Intelligence 135

Business Intelligence Data mining Machine Learning Testing 135

Alation

FEBRUARY 20, 2020

For ease of understanding the differences between all of the them Rita shared this visual, categorizing the vendors: So at least for now, it looks like we’re a self-service data prep vendor, which makes sense. Alation helps analysts find, understand and use their data. Definitely one of the best presentations of the week!

Scorecard 52

Scorecard ROI Data-driven Visualization 52

AWS Big Data

MARCH 13, 2024

You can also use the data transformation feature of Data Firehose to invoke a Lambda function to perform data transformation in batches. Data enrichment using Lambda Data enrichment in this pattern is facilitated through the invocation of a Lambda function.

Analytics 90

Analytics IoT Metadata Internet of Things 90

AWS Big Data

JULY 26, 2023

The code includes the following: AWS resource definition Data integration logic When using AWS Glue, you can define the data integration logic in a job script, which can be written in Python or Scala. They analyze the requirements to identify coding tasks to achieve the final result.

Data Integration 69

Data Integration Snapshot Testing Visualization 69

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.

Analytics 59

Analytics Reporting Dashboards Visualization 59

erwin

JANUARY 11, 2019

Organizations have spent a lot of time and money trying to harmonize data across diverse platforms , including cleansing, uploading metadata, converting code, defining business glossaries, tracking data transformations and so on. If you want more control over and more value from all your data, join us for a demo of erwin MM.

Data Governance 40

Data Governance Risk Metadata Management 40

Cloudera

JUNE 1, 2021

These acquisitions usher in a new era of “ self-service ” by automating complex operations so customers can focus on building great data-driven apps instead of managing infrastructure. Datacoral powers fast and easy data transformations for any type of data via a robust multi-tenant SaaS architecture that runs in AWS.

Uncertainty 144

Uncertainty Cost-Benefit Risk Strategy 144

Octopai

DECEMBER 11, 2022

It’s for that reason that even as the first BCBS-239 implementation deadline came into effect a few years ago, McKinsey reported that one-third of Global Systemically Important Banks had focused on “documenting data lineage up to the level of provisioning data elements and including data transformation.”.

Insurance 52

Insurance Risk Metadata Reporting 52

FineReport

MARCH 7, 2024

Data Analysis Report (by FineReport ) Note: All the data analysis reports in this article are created using the FineReport reporting tool. Leveraging the advanced enterprise-level web reporting tool capabilities of FineReport , we empower businesses to achieve genuine data transformation. Try FineReport Now 1.

Dashboards 52

Dashboards Reporting Advertising Statistics 52

AWS Big Data

MAY 16, 2023

Amazon Kinesis Data Streams interacts with the third-party application through a native connection and conducts necessary data transformation in real time, and Amazon Kinesis Data Firehose stores the data in Amazon Simple Storage Service (Amazon S3) buckets.

Dashboards 74

Dashboards Statistics Data Collection Business Intelligence 74

Ontotext

APRIL 4, 2019

We apply Artificial Intelligence techniques to understand the value locked in this data so we can extract knowledge that can benefit people. Milena Yankova : There are two definitions of Artificial Intelligence. One area where computers will definitely not replace us is our creativity. But that doesn’t worry me too much.

Recreation/Entertainment 76

Recreation/Entertainment Testing Enterprise Knowledge Discovery 76

AWS Big Data

APRIL 25, 2024

Alternatively, you can use AWS Glue for Apache Spark, which provides built-in support for bucketing configurations during the data transformation process. AWS Glue allows you to define bucketing parameters, such as the number of buckets and the columns to bucket on, providing an optimized data layout for efficient querying with Athena.

Optimization 65

Optimization Data Lake Cost-Benefit Reporting 65

DataKitchen

DECEMBER 9, 2022

The data scientists and IT professionals were starting to get frustrated, when suddenly, a magical fairy appeared out of nowhere. The fairy was carrying a DataOps wand, and she waved it over the messy data, transforming it into a clean and organized dataset.

Machine Learning 130

Machine Learning Data-driven Optimization Modeling 130

AWS Big Data

FEBRUARY 6, 2023

We then discuss a solution to further enhance end-to-end observability by modifying the task definitions that make up the data pipeline. For this post, we focus on task definitions for two services: AWS Glue and Amazon EMR­, however the same method can be applied across different services.

Management 81

Management Interactive Metadata Publishing 81

erwin

MARCH 4, 2021

Led by Frank Pörschmann of iDIGMA GmbH, an IT industry veteran and data governance strategist, it examined “ The What & Why of Data Governance.”. The What: Data Governance Defined. Data governance has no standard definition. But he cautions “this [notion] is something which is not really likely to happen.”.

Data Governance 122

Data Governance Digital Transformation Data-driven Cost-Benefit 122

AWS Big Data

NOVEMBER 15, 2023

It works as a bundle for resources that are bound to a specific staging environment and Region to store data on Amazon Simple Storage Service (Amazon S3), which is renowned for its industry-leading scalability, data availability, security, and performance. Data providers and consumers are the two fundamental users of a CDH dataset.

Dashboards 91

Dashboards Analytics Metadata Data Warehouse 91

AWS Big Data

SEPTEMBER 6, 2023

Stored procedures are commonly used to encapsulate logic for data transformation, data validation, and business-specific logic. However, the primaryphone update will not roll back because it ran in its own implicit transaction block due to the NONATOMIC clause in the stored procedure definition.

Data Warehouse 92

Data Warehouse Insurance Statistics Software 92

Alation

OCTOBER 18, 2022

Yet every dbt transformation contains vital metadata that is not captured – until now. Making this data visible in the data catalog will let data teams share their work, support re-use, and empower everyone to better understand and trust data. Data Transformation in the Modern Data Stack.

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

O'Reilly on Data

OCTOBER 19, 2021

While there isn’t an authoritative definition for the term, it shares its ethos with its predecessor, the DevOps movement in software engineering: by adopting well-defined processes, modern tooling, and automated workflows, we can streamline the process of moving from development to robust production deployments. Model Development.

IT 346

IT Testing Experimentation Software 346

Alation

JANUARY 17, 2023

You should look for a data warehouse that is scalable, flexible, and efficient. Popular cloud data warehouses today include Snowflake, Databricks, and BigQuery. If your organization is large, you definitely need to look for robustness. Good data warehouses should be reliable. How Can I Build a Modern Data Stack?

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Business Intelligence 52

Alation

AUGUST 11, 2022

But there are only so many data engineers available in the market today; there’s a big skills shortage. So to get away from that lack of data engineers, what data mesh says is, ‘Take those business logic data transformation capabilities and move that to the domains.’ But “customer” is an easy one.

Metadata 52

Metadata Data Warehouse Data Quality Data Lake 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.

Modeling 69

Modeling Metadata Data Quality Enterprise 69

Anmut

APRIL 6, 2022

Data is definitely not a traditional corporate asset. So what do we mean by the term ‘data asset’? We’re happy to explain, starting with some quick definitions of a few relevant terms. A data element is a defined unit of data such as date, account number, temperature, name, item description, etc.

Cost-Benefit 52

Cost-Benefit ROI Sales Data-driven 52

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 Data Catalog now contains references to the machine-readable data. Use the Data Catalog and transform the hospital price transparency data.

Visualization 92

Visualization Dashboards Data-driven Gap analysis 92

O'Reilly on Data

JANUARY 17, 2023

Instead of invoking the open-source scikit-learn or Keras calls to build models, your team now goes from Pandas data transforms straight to … the API calls for AWS AutoPilot or GCP Vertex AI. It does not exist in the code. AutoML drives this point home. And it’s available to everyone.

Machine Learning 325

Machine Learning Predictive Modeling Software Modeling 325

Ontotext

DECEMBER 9, 2020

If you have ever built your own custom GraphQL API layer, the code typically resolves each part of a GraphQL query as it traverses downwards as a separate isolated data fetching step. This leads to lots of small data fetches to/from GraphDB over the network. Custom code also tends to over-fetch data that is not required.

Modeling 130

Modeling Management Optimization Metrics 130

IBM Big Data Hub

JANUARY 18, 2023

This adds an additional ETL step, making the data even more stale. Data lakehouse was created to solve these problems. The data warehouse storage layer is removed from lakehouse architectures. Instead, continuous data transformation is performed within the BLOB storage. It is narrower in focus than data fabric.

Data Lake 52

Data Lake Data Warehouse Data-driven Metadata 52

DataRobot Blog

APRIL 4, 2022

Data Requirements. As with any type of statistical model, data is key and GIGO (“Garbage In, Garbage Out”) principle definitely applies. Historical data needs to be accurate, consistent and, most importantly, available.

Machine Learning 52

Machine Learning Sales Measurement ROI 52

AWS Big Data

JUNE 29, 2023

Kinesis Data Analytics for Apache Flink In our example, we perform the following actions on the streaming data: Connect to an Amazon Kinesis Data Streams data stream. View the stream data. Transform and enrich the data. Manipulate the data with Python.

Data Analytics 71

Data Analytics Analytics IoT Data Lake 71

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 98

Data Lake Management Metrics Data Warehouse 98

erwin

APRIL 16, 2024

Gathering this data isn’t possible without automation. erwin Data Intelligence has the functionality to scan the organization’s data estate and capture metadata about all data held in databases. With access rights, data stewards can be restricted to access just the data sets within their scope of responsibility.

Metadata 52

Metadata Data Quality Data Governance Modeling 52