Smart Data Collective

JUNE 7, 2019

This is where real-time stream processing enters the picture, and it may probably change everything you know about big data. Read this article as we’ll tackle what big data and stream processing are. We’ll also deal with how big data stream processing can help new emerging markets in the world.

Big Data 81

Big Data Marketing Cost-Benefit Unstructured Data 81

CIO Business Intelligence

OCTOBER 13, 2023

Data architect Armando Vázquez identifies eight common types of data architects: Enterprise data architect: These data architects oversee an organization’s overall data architecture, defining data architecture strategy and designing and implementing architectures.

Data Architecture 122

Data Architecture Data Warehouse Statistics Visualization 122

AWS Big Data

JUNE 28, 2023

There are two broad approaches to analyzing operational data for these use cases: Analyze the data in-place in the operational database (e.g. With Aurora zero-ETL integration with Amazon Redshift, the integration replicates data from the source database into the target data warehouse.

Data Warehouse 87

Data Warehouse Analytics Metrics Dashboards 87

Sisense

MARCH 20, 2019

To do that, a data engineer needs to be skilled in a variety of platforms and languages. In our never-ending quest to make BI better, we took it upon ourselves to list the skills and tools every data engineer needs to tackle the ever-growing pile of Big Data that every company faces today. Data Warehousing.

Big Data 72

Big Data Machine Learning Data Warehouse Unstructured Data 72

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

AWS Big Data

JULY 27, 2023

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, easy, and secure analytics at scale. Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the widely used cloud data warehouse.

Data Warehouse 86

Data Warehouse Analytics Metadata Dashboards 86

AWS Big Data

MAY 16, 2024

For more information or to get started with Amazon Redshift spatial analytics, see the documentation for querying spatial data , spatial functions , and the spatial tutorial. It delivers this at a price performance that’s up to three times better than other cloud data warehouses out of the box, helping you keep your costs predictable.

Data Warehouse 109

Data Warehouse Visualization Cost-Benefit Optimization 109

Sisense

SEPTEMBER 3, 2019

This blog is intended to give an overview of the considerations you’ll want to make as you build your Redshift data warehouse to ensure you are getting the optimal performance. This results in less joins between the metric data in fact tables, and the dimensions. So let’s dive in! OLTP vs OLAP. Sort & Dist Keys.

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

AWS Big Data

MAY 16, 2024

It involves performing a full load of Amazon DocumentDB data and continuously streaming the latest data to Amazon OpenSearch Service using change streams. For other ingestion methods, see documentation. Insert some documents into the collection product in the inventory database by running the following commands.

Data Processing 106

Data Processing Data Warehouse Management Metrics 106

AWS Big Data

NOVEMBER 29, 2023

As part of the Talent Intelligence Platform Eightfold also exposes a data hub where each customer can access their Amazon Redshift-based data warehouse and perform ad hoc queries as well as schedule queries for reporting and data export. Many customers have implemented Amazon Redshift to support multi-tenant applications.

Metadata 103

Metadata Data Warehouse Analytics Data Analytics 103

Cloudera

DECEMBER 12, 2018

After having rebuilt their data warehouse, I decided to take a little bit more of a pointed role, and I joined Oracle as a database performance engineer. I spent eight years in the real-world performance group where I specialized in high visibility and high impact data warehousing competes and benchmarks. Interesting times.

Data Warehouse 42

Data Warehouse Marketing Big Data Data Lake 42

AWS Big Data

FEBRUARY 29, 2024

Data governance is a critical building block across all these approaches, and we see two emerging areas of focus. First, many LLM use cases rely on enterprise knowledge that needs to be drawn from unstructured data such as documents, transcripts, and images, in addition to structured data from data warehouses.

Data Governance 97

Data Governance Unstructured Data Metadata Data Lake 97

AWS Big Data

MAY 3, 2023

In today’s data-driven business environment, organizations face the challenge of efficiently preparing and transforming large amounts of data for analytics and data science purposes. Businesses need to build data warehouses and data lakes based on operational data.

Data Lake 80

Data Lake Data Warehouse Data-driven Optimization 80

AWS Big Data

APRIL 30, 2024

It can generate data integration jobs for extracts and loads to S3 data lakes including file formats like CSV, JSON, and Parquet, and ingestion into open table formats like Apache Hudi, Delta, and Apache Iceberg. These capabilities simplify and accelerate data processing and integration on AWS.

Data Integration 104

Data Integration Data Lake Data Warehouse Software 104

Cloudera

AUGUST 31, 2021

Cloudera and Accenture demonstrate strength in their relationship with an accelerator called the Smart Data Transition Toolkit for migration of legacy data warehouses into Cloudera Data Platform. Accenture’s Smart Data Transition Toolkit . Are you looking for your data warehouse to support the hybrid multi-cloud?

Data Warehouse 82

Data Warehouse Cost-Benefit Metadata Data-driven 82

AWS Big Data

MARCH 20, 2024

To run analytics on your operational data, you might build a solution that is a combination of a database, a data warehouse, and an extract, transform, and load (ETL) pipeline. ETL is the process data engineers use to combine data from different sources.

Data Warehouse 124

Data Warehouse Business Driver Data Lake Data-driven 124

Smart Data Collective

SEPTEMBER 26, 2021

Working with massive structured and unstructured data sets can turn out to be complicated. It’s obvious that you’ll want to use big data, but it’s not so obvious how you’re going to work with it. So, let’s have a close look at some of the best strategies to work with large data sets. A document is susceptible to change.

Metadata 98

Metadata Visualization Unstructured Data Data mining 98

AWS Big Data

JULY 25, 2023

The integration of Talend Cloud and Talend Stitch with Amazon Redshift Serverless can help you achieve successful business outcomes without data warehouse infrastructure management. In this post, we demonstrate how Talend easily integrates with Redshift Serverless to help you accelerate and scale data analytics with trusted data.

Data Analytics 52

Data Analytics Data Warehouse Analytics Data Processing 52

AWS Big Data

NOVEMBER 9, 2023

This popular open-source tool for data warehouse transformations won out over other ETL tools for several reasons. The tool also offered desirable out-of-the-box features like data lineage, documentation, and unit testing. AWS Glue is a fully managed ETL service that makes it easy to prepare and load data for analysis.

Data Warehouse 106

Data Warehouse Testing Data Quality Reporting 106

AWS Big Data

MARCH 1, 2024

One of the bank’s key challenges related to strict cybersecurity requirements is to implement field level encryption for personally identifiable information (PII), Payment Card Industry (PCI), and data that is classified as high privacy risk (HPR). Only users with required permissions are allowed to access data in clear text.

Data Lake 101

Data Lake Data Warehouse Management Risk 101

AWS Big Data

MARCH 2, 2023

Amazon Redshift is a fully managed, petabyte-scale data warehouse service in the cloud. Amazon Redshift enables you to use SQL for analyzing structured and semi-structured data with best price performance along with secure access to the data.

Visualization 81

Visualization Dashboards Data Warehouse Metrics 81

AWS Big Data

OCTOBER 5, 2023

Amazon AppFlow , a fully managed data integration service, has been at the forefront of streamlining data transfer between AWS services, software as a service (SaaS) applications, and now Google BigQuery. Architecture Let’s review the architecture to transfer data from Google BigQuery to Amazon S3 using Amazon AppFlow.

Data Warehouse 87

Data Warehouse Machine Learning Data Integration Data-driven 87

AWS Big Data

MARCH 27, 2024

Amazon Redshift is a fast, scalable, and fully managed cloud data warehouse that allows you to process and run your complex SQL analytics workloads on structured and semi-structured data. The scope should contain inputs and data points on the current architecture as well as the target architecture.

Testing 100

Testing Data Warehouse Metrics Cost-Benefit 100

IBM Big Data Hub

MAY 9, 2023

is not just for data scientists and developers — business users can also access it via an easy-to-use interface that responds to natural language prompts for different tasks. With watsonx.data , businesses can quickly connect to data, get trusted insights and reduce data warehouse costs. Watsonx.ai

Data Warehouse 107

Data Warehouse Machine Learning Cost-Benefit Metadata 107

AWS Big Data

OCTOBER 20, 2023

Noritaka Sekiyama is a Principal Big Data Architect on the AWS Glue team. He is passionate about architecting fast-growing data environments, diving deep into distributed big data software like Apache Spark, building reusable software artifacts for data lakes, and sharing knowledge in AWS Big Data blog posts.

Data Lake 86

Data Lake Big Data Consulting Data Warehouse 86

AWS Big Data

NOVEMBER 30, 2023

This integration simplifies the authentication and authorization process for Amazon Redshift users using Query Editor V2 or Amazon Quicksight , making it easier for them to securely access your data warehouse. Note: Your organization’s IdC instance must be in the same region as the Amazon Redshift data warehouse you’re connecting to.

Data Warehouse 83

Data Warehouse Finance Sales Management 83

Alation

JANUARY 17, 2023

It is known to have benefits in handling data due to its robustness, speed, and scalability. A typical modern data stack consists of the following: A data warehouse. Data ingestion/integration services. Data orchestration tools. In the past, data movement was defined by ETL: extract, transform, and load.

Data Warehouse 52

Data Warehouse Cost-Benefit Data Transformation Data Science 52

AWS Big Data

MARCH 25, 2024

A RAG-based generative AI application can only produce generic responses based on its training data and the relevant documents in the knowledge base. For example, Amazon DynamoDB provides a feature for streaming CDC data to Amazon DynamoDB Streams or Kinesis Data Streams.

Data Lake 91

Data Lake Unstructured Data Management Modeling 91

erwin

FEBRUARY 13, 2020

The numerous data types and data sources that exist today weren’t designed to work together, and data infrastructures have been cobbled together over time with disparate technologies, poor documentation and little thought for downstream integration. Finding metadata, “the data about the data,” isn’t easy.

Metadata 135

Metadata Data Governance Management Cost-Benefit 135

AWS Big Data

NOVEMBER 16, 2023

Amazon Redshift is a popular cloud data warehouse, offering a fully managed cloud-based service that seamlessly integrates with an organization’s Amazon Simple Storage Service (Amazon S3) data lake, real-time streams, machine learning (ML) workflows, transactional workflows, and much more—all while providing up to 7.9x

Enterprise 86

Enterprise Data Warehouse Snapshot Cost-Benefit 86

AWS Big Data

JANUARY 24, 2024

These formats enable ACID (atomicity, consistency, isolation, durability) transactions, upserts, and deletes, and advanced features such as time travel and snapshots that were previously only available in data warehouses. resource('s3') bucket = s3.Bucket(' Bucket(' ') bucket.objects.filter(Prefix=" /noaadelta/").delete()

Snapshot 102

Snapshot Data Lake Metadata Optimization 102

datapine

FEBRUARY 22, 2022

Over the past 5 years, big data and BI became more than just data science buzzwords. Without real-time insight into their data, businesses remain reactive, miss strategic growth opportunities, lose their competitive edge, fail to take advantage of cost savings options, don’t ensure customer satisfaction… the list goes on.

Business Intelligence 218

Business Intelligence Strategy Cost-Benefit Key Performance Indicator 218

AWS Big Data

MARCH 11, 2024

Amazon Redshift is a fully managed, scalable cloud data warehouse that accelerates your time to insights with fast, straightforward, and secure analytics at scale. Tens of thousands of customers rely on Amazon Redshift to analyze exabytes of data and run complex analytical queries, making it the most widely used cloud data warehouse.

Analytics 65

Analytics Data Warehouse Optimization Metrics 65

datapine

NOVEMBER 19, 2019

In this day and age, we’re all constantly hearing the terms “big data”, “data scientist”, and “in-memory analytics” being thrown around. Almost all the major software companies are continuously making use of the leading Business Intelligence (BI) and Data discovery tools available in the market to take their brand forward.

Business Intelligence 146

Business Intelligence Knowledge Discovery Dashboards Unstructured Data 146

AWS Big Data

APRIL 3, 2023

Tens of thousands of customers run business-critical workloads on Amazon Redshift , AWS’s fast, petabyte-scale cloud data warehouse delivering the best price-performance. With Amazon Redshift, you can query data across your data warehouse, operational data stores, and data lake using standard SQL.

Data Warehouse 99

Data Warehouse Testing Data Lake Data-driven 99

erwin

SEPTEMBER 25, 2020

Understanding the benefits of data modeling is more important than ever. Data modeling is the process of creating a data model to communicate data requirements, documenting data structures and entity types. In addition, erwin DM users have the ability to: Visualize any data, from anywhere.

Modeling 111

Modeling Cost-Benefit Visualization Metadata 111

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. How to scale AL and ML with built-in governance A fit-for-purpose data store built on an open lakehouse architecture allows you to scale AI and ML while providing built-in governance tools.

Risk 72

Risk Modeling Management Metadata 72