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 80

Enterprise Data Warehouse Snapshot Cost-Benefit 80

AWS Big Data

MARCH 7, 2023

Data lakes are more focused around storing and maintaining all the data in an organization in one place. And unlike data warehouses, which are primarily analytical stores, a data hub is a combination of all types of repositories—analytical, transactional, operational, reference, and data I/O services, along with governance processes.

Analytics 68

Analytics Data Warehouse Data Lake Metadata 68

AWS Big Data

MARCH 7, 2024

At the same time, they need to optimize operational costs to unlock the value of this data for timely insights and do so with a consistent performance. With this massive data growth, data proliferation across your data stores, data warehouse, and data lakes can become equally challenging.

Data Lake 109

Data Lake Analytics Dashboards Metrics 109

Cloudera

MAY 17, 2021

In this blog, we’ll cover the complete range of new capabilities and updates for CDP Private Cloud as a whole (the platform) as well as for both the CDW (Cloudera Data Warehouse) and CML (Cloudera Machine Learning) services. Additional database metrics were added and alerts were improved. documentation. Private Cloud 1.2

Machine Learning 89

Machine Learning Data Warehouse Data-driven Metrics 89

CIO Business Intelligence

JUNE 7, 2022

A data scientist is a mix of a product analyst and a business analyst with a pinch of machine learning knowledge, says Mark Eltsefon, data scientist at TikTok. AI strategists can also help organizations obtain the data they need to fuel AI effectively.

Machine Learning 145

Machine Learning Data Science Consulting Metrics 145

Ontotext

MAY 2, 2024

Storage-centric approach In the storage-centric approach, people try to address data silos by throwing everything in a data lake or a data warehouse. But, although, this helps somewhat in terms of architecture, soon these data lakes become unwieldy.

Metadata 52

Metadata Data Lake Data-driven Enterprise 52

Jet Global

OCTOBER 7, 2020

Confusing matters further, Microsoft has also created something called the Data Entity Store, which serves a different purpose and functions independently of data entities. The Data Entity Store is an internal data warehouse that is only available to embedded Power BI reports (not the full version of Power BI).

Data Warehouse 90

Data Warehouse OLAP Reporting Finance 90

Jet Global

MAY 1, 2020

They are going to have different ways of combining numbers into metrics. We can almost guarantee you different results from each, and you end up with no data integrity whatsoever. The mechanical solution is to build a data warehouse. For example: How do we want our data to be structured? Risk to the business.

Data Warehouse 64

Data Warehouse Data Quality Risk Reporting 64

erwin

MARCH 8, 2019

Therefore, the organization needed to catalog the data it acquires from suppliers, ensure its quality, classify it, and then sell it to customers. The company wanted to assemble the data in a data warehouse and then provide controlled access to it.

Data Governance 65

Data Governance Metadata Data Warehouse Data Quality 65

Octopai

JUNE 1, 2020

Implementing good data mapping practices is an important way modern enterprise organizations use advanced business metrics for strategic insight. With the rapid rise of new data regulations across the globe, capable data mapping isn’t just a tool for companies to get a leg up on the competition – it is required for legal compliance.

Metadata 52

Metadata Data Warehouse Data Integration Finance 52

AWS Big Data

FEBRUARY 8, 2023

A major challenge with ServiceMax implementation is building a data pipeline between ERP and the ServiceMax application, precisely integrating pricing, orders, and primary data (product, customer) from SAP ERP to ServiceMax using Vyaire’s custom-built integration platform iDataHub.

Testing 70

Testing Data Integration Data Lake Enterprise 70

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. or higher version) database.

Data Warehouse 81

Data Warehouse Analytics Metrics Dashboards 81

Cloudera

MAY 22, 2018

With CDSW, organizations can research and experiment faster, deploy models easily and with confidence, as well as rely on the wider Cloudera platform to reduce the risks and costs of data science projects. track model metrics, performance, and any model artifacts the user specifies. let the user document, test, and share the model.

Data Science 41

Data Science Snapshot Machine Learning Metadata 41

Alation

SEPTEMBER 7, 2021

With Snowflake, data stewards have a choice to leverage Snowflake’s governance policies. First, stewards are dependent on data warehouse admins to provide information and to create and edit enforcement policies in Snowflake. Operationalize data governance at scale. Two problems arise. In Summary.

Data Governance 59

Data Governance Risk Data Quality Dashboards 59

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 119

Data Warehouse Business Driver Data Lake Data-driven 119

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

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. Think of it like something that houses the metrics used to power daily, weekly, or monthly business KPIs. roll-ups of many rows of data).

Data Warehouse 78

Data Warehouse OLAP Statistics Cost-Benefit 78

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 75

Visualization Dashboards Data Warehouse Metrics 75

Alation

OCTOBER 27, 2022

Few actors in the modern data stack have inspired the enthusiasm and fervent support as dbt. This data transformation tool enables data analysts and engineers to transform, test and document data in the cloud data warehouse. This graph is an example of one analysis, documented in our internal catalog.

Metrics 52

Metrics Dashboards Sales Reporting 52

FineReport

APRIL 11, 2023

Free Download of FineReport What is Business Intelligence Dashboard (BI Dashboard)？ A business intelligence dashboard, also known as a BI dashboard, is a tool that presents important business metrics and data points in a visual and analytical format on a single screen.

Dashboards 40

Dashboards Business Intelligence Cost-Benefit Metrics 40

Occam's Razor

SEPTEMBER 20, 2010

Segment them in your data, the delightful numbers you see in your KPI's will show you why. So if Direct traffic is so important and often the metrics show very positive results then why don't we all obsess about it a lot more? You goal is to get people to buy your Discover data warehouse product.

Analytics 122

Analytics Metrics Data-driven Reporting 122

Alation

OCTOBER 18, 2022

Alation is pleased to be named a dbt Metrics Partner and to announce the start of a partnership with dbt, which will bring dbt data into the Alation data catalog. In the modern data stack, dbt is a key tool to make data ready for analysis. But what if you could combine that information with usage metrics?

Metadata 52

Metadata Metrics Recreation/Entertainment Data Quality 52

AWS Big Data

JUNE 6, 2023

However, these tools often require manual processes of data discovery and expertise in data engineering and coding. AWS Glue Data Quality is a new feature of AWS Glue that measures and monitors the data quality of Amazon Simple Storage Service (Amazon S3)-based data lakes, data warehouses, and other data repositories.

Data Quality 71

Data Quality Data Lake Data-driven Metrics 71

Alation

MAY 24, 2022

Meanwhile, new data quality vendors have been making significant advances. New features include: Rules — Validate data is correct, for example by checking if postal codes in the U.S. Metrics — Profile data to provide a sense of it, such as checking for nulls and blanks to ensure data exists.

Data Quality 98

Data Quality Data Governance Metadata Metrics 98

Alation

JULY 19, 2022

For example, a new data scientist who is curious about which customers are most likely to be repeat buyers, might search for customer data only to discover an article documenting a previous project that answered their exact question. Finally, data catalogs can help data scientists promulgate the results of their projects.

Metadata 59

Metadata Data Quality Statistics Data Science 59

Occam's Razor

JANUARY 24, 2011

Surely not using horrible metrics like Page Views, right? You will only create a data-driven organization when you are able to compute the complete economic value created by the website. Not through data pukes. You'll need to look in your corporate data warehouses. It is easy and it is hard. That's done.

Analytics 122

Analytics Finance B2B ROI 122

Ontotext

OCTOBER 14, 2021

For the purposes of this article, you just need to know the following: A graph is a method of storing and modeling data that uniquely captures the relationships between data. A knowledge graph uses this format to integrate data from different sources while enriching it with metadata that documents collective knowledge about the data.

Reporting 98

Reporting Structured Data Metadata Data Warehouse 98

CIO Business Intelligence

SEPTEMBER 21, 2022

“While the passage and enforcement of GDPR, CCPA in California, and other data regulations may have once been seen as seismic events affecting brands and publishers alike, they’ve actually been a forcing function for companies to organize their data, remove data silos, and clearly document what they have access to and how it can be used.”.

Risk 104

Risk Data Lake Marketing Interactive 104

Corinium

APRIL 25, 2019

For example, P&C insurance strives to understand its customers and households better through data, to provide better customer service and anticipate insurance needs, as well as accurately measure risks. Life insurance needs accurate data on consumer health, age and other metrics of risk.

Insurance 150

Insurance Risk IoT Cost-Benefit 150

IBM Big Data Hub

OCTOBER 12, 2023

To optimize data analytics and AI workloads, organizations need a data store built on an open data lakehouse architecture. This type of architecture combines the performance and usability of a data warehouse with the flexibility and scalability of a data lake.

Cost-Benefit 82

Cost-Benefit Metadata Data Governance Modeling 82

Smart Data Collective

FEBRUARY 20, 2022

Different DAM providers use different approaches to defining the key metrics that influence the cost of an off-the-shelf solution. In addition, well-known products boast a lot of implementations and use cases that are comprehensively reflected in the documentation. Stopping insiders in their tracks.

Behavioral Analytics 118

Behavioral Analytics Risk Machine Learning Interactive 118

Cloudera

OCTOBER 25, 2022

Cloud data lakehouses provide significant scaling, agility, and cost advantages compared to cloud data lakes and cloud data warehouses. They combine the best of both worlds: flexibility, cost effectiveness of data lakes and performance, and reliability of data warehouses.”. Authorization.

Data Processing 52

Data Processing Data Lake Cost-Benefit Risk 52

datapine

AUGUST 29, 2022

Whether you are a complete novice or a seasoned BI professional, you will find here some books on data analytics that will help you cultivate your understanding of this essential field. Before we delve deeper into the best books for data analytics, here are three big data insights to put their relevance and importance into perspective.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

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

AWS Big Data

MARCH 3, 2023

It has been well published since the State of DevOps 2019 DORA Metrics were published that with DevOps, companies can deploy software 208 times more often and 106 times faster, recover from incidents 2,604 times faster, and release 7 times fewer defects. Ricardo Serafim is a Senior AWS Data Lab Solutions Architect.

Software 52

Software Data Lake Testing Cost-Benefit 52

AWS Big Data

JUNE 9, 2023

A modern data architecture enables companies to ingest virtually any type of data through automated pipelines into a data lake, which provides highly durable and cost-effective object storage at petabyte or exabyte scale.

Data Lake 109

Data Lake Metadata Optimization Statistics 109

Smart Data Collective

JUNE 6, 2021

Customer experience is another key area that can benefit from big data analytics. The collection and use of relevant metrics can, therefore, potentially boost your chances of engaging new prospects while keeping existing customers satisfied. Big data analytics advantages. What is Big Data?” What is Google BigQuery?

Big Data 134

Big Data Data Analytics Analytics Cost-Benefit 134