Dataversity

DECEMBER 12, 2022

When it comes to data sources, analytic apps developers are facing new and increasingly complex challenges, such as having to deal with higher demand from event data and streaming sources. The post Is Your Database Built for Streaming Data? Yet while streams are clearly the […].

Database 52

Database Analytics Analytics Data Warehouse 52

Dataconomy

SEPTEMBER 4, 2023

Diagnostic analytics: Diagnostic analytics goes a step further by analyzing historical data to determine why certain events occurred. By understanding the “why” behind past events, organizations can make informed decisions to prevent or replicate them. Ensure that data is clean, consistent, and up-to-date.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

phData

MARCH 7, 2023

The task of keeping multiple databases in sync so that data is accurate, up-to-date, and highly available is every data consumer’s biggest challenge. Oracle is one of the largest IT companies whose flagship product, Oracle Database, is a relational database management system. What is Oracle?

Hadoop 59

Hadoop Database Data Warehouse AWS 59

Flipboard

DECEMBER 6, 2023

The Q4 Platform facilitates interactions across the capital markets through IR website products, virtual events solutions, engagement analytics, investor relations Customer Relationship Management (CRM), shareholder and market analysis, surveillance, and ESG tools. Use case overview Q4 Inc.,

SQL 168

SQL Database AWS Machine Learning 168

Dataconomy

JUNE 1, 2023

This open format allows for seamless storage and retrieval of data across different databases. By automating the integration of all Fabric workloads into OneLake, Microsoft eliminates the need for developers, analysts, and business users to create their own data silos.

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Power BI Data Lakes Azure Data Silos 194

phData

MARCH 7, 2023

Snowflake’s solution to this was to create a Streaming API that can be used to connect and write directly to the database using your own managed application, which lowers latency and removes the requirement of storing files in a stage. Next, we create a request and we set the Database, Schema, and Table that the request should point at.

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Data Warehouse Database 98

IBM Journey to AI blog

SEPTEMBER 11, 2023

Thus, was born a single database and the relational model for transactions and business intelligence. Its early success, coupled with IBM WebSphere in the 1990s, put it in the spotlight as the database system for several Olympic games, including 1992 Barcelona, 1996 Atlanta, and the 1998 Winter Olympics in Nagano.

Database 101

Database SQL Data Warehouse Machine Learning 101

Hacker News

AUGUST 27, 2024

Batch-processing systems that process data rows in batch (mainly via SQL ). Examples include real-time and data warehouse systems that power Meta’s AI and analytics workloads. Data annotation can be done at various levels of granularity, including table, column, row, or potentially even cell.

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Data Warehouse Database SQL Machine Learning 166

IBM Journey to AI blog

OCTOBER 30, 2023

Overall, this partnership enables the retailer to make data-driven decisions, improve supply chain efficiency and ultimately boost customer satisfaction, all in a secure and scalable cloud environment. The platform provides an intelligent, self-service data ecosystem that enhances data governance, quality and usability.

AWS 95

AWS AI Data Warehouse AI 95

Mlearning.ai

MAY 16, 2023

It is used to extract data from various sources, transform the data to fit a specific data model or schema, and then load the transformed data into a target system such as a data warehouse or a database. First, the data is extracted from the various sources and brought into a staging area.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

phData

APRIL 29, 2024

Recognizing these specific needs, Fivetran has developed a range of connectors, including dedicated applications, databases, files, and events, which can accommodate the diverse formats used by healthcare systems. Some even provide a relational layer specifically designed for analytics, while others expose APIs.

SQL 52

SQL Data Warehouse Azure Cloud Data 52

Pickl AI

MARCH 19, 2025

Without data engineering , companies would struggle to analyse information and make informed decisions. What Does a Data Engineer Do? A data engineer creates and manages the pipelines that transfer data from different sources to databases or cloud storage. How is Data Engineering Different from Data Science?

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Mlearning.ai

FEBRUARY 16, 2023

The ultimate need for vast storage spaces manifests in data warehouses: specialized systems that aggregate data coming from numerous sources for centralized management and consistency. In this article, you’ll discover what a Snowflake data warehouse is, its pros and cons, and how to employ it efficiently.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

AWS Machine Learning Blog

JULY 17, 2023

Amazon Redshift is a fully managed, fast, secure, and scalable cloud data warehouse. Organizations often want to use SageMaker Studio to get predictions from data stored in a data warehouse such as Amazon Redshift. On the Name, review, and create page, enter a role name, review the settings, and choose Create role.

Clustering 97

Clustering AWS ML ML 97

phData

FEBRUARY 14, 2023

Data integration is essentially the Extract and Load portion of the Extract, Load, and Transform (ELT) process. Data ingestion involves connecting your data sources, including databases, flat files, streaming data, etc, to your data warehouse. Snowflake provides native ways for data ingestion.

Data Warehouse 59

Data Warehouse Azure AWS Database 59

Pickl AI

JULY 25, 2024

Must Read Blogs: Exploring the Power of Data Warehouse Functionality. Data Lakes Vs. Data Warehouse: Its significance and relevance in the data world. Exploring Differences: Database vs Data Warehouse. It is commonly used in data warehouses for business analytics and reporting.

Data Warehouse 52

Data Warehouse Business Intelligence Business Intelligence Database 52

IBM Journey to AI blog

SEPTEMBER 19, 2023

And you should have experience working with big data platforms such as Hadoop or Apache Spark. Additionally, data science requires experience in SQL database coding and an ability to work with unstructured data of various types, such as video, audio, pictures and text.

Data Science 94

Data Science Analytics Analytics Data Scientist 94

ODSC - Open Data Science

JANUARY 30, 2024

Building and maintaining data pipelines Data integration is the process of combining data from multiple sources into a single, consistent view. This involves extracting data from various sources, transforming it into a usable format, and loading it into data warehouses or other storage systems.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Precisely

JANUARY 25, 2024

There are three potential approaches to mainframe modernization: Data Replication creates a duplicate copy of mainframe data in a cloud data warehouse or data lake, enabling high-performance analytics virtually in real time, without negatively impacting mainframe performance. Best Practice 5.

Data Governance 69

Data Governance Database Cloud Data Data Lakes 69

Pickl AI

NOVEMBER 4, 2024

Role of Data Engineers in the Data Ecosystem Data Engineers play a crucial role in the data ecosystem by bridging the gap between raw data and actionable insights. They are responsible for building and maintaining data architectures, which include databases, data warehouses, and data lakes.

Data Engineering 52

Data Engineering Data Engineering Data Engineering Data Engineer 52

Alation

DECEMBER 14, 2021

With the database services launched soon after, developers had all the tools they needed to create applications without having to create the infrastructure to run them. AWS positions itself as an end-to-end solution with full integration of BI, ML, storage and database tools, and customer stories support this.

AWS 52

AWS Data Lakes Data Warehouse Machine Learning 52

phData

OCTOBER 20, 2023

Production databases are a data-rich environment, and Fivetran would help us to migrate data by moving data from on-prem to the supported destinations; ensuring that this data remains uncorrupted throughout enhancements and transformations is crucial. We will now go over all the topics one by one.

Database 52

Database SQL ETL Data Warehouse 52

IBM Journey to AI blog

OCTOBER 16, 2023

Curated foundation models, such as those created by IBM or Microsoft, help enterprises scale and accelerate the use and impact of the most advanced AI capabilities using trusted data. In addition to natural language, models are trained on various modalities, such as code, time-series, tabular, geospatial and IT events data.

AI 88

AI AI Data Warehouse ML 88

phData

MARCH 11, 2024

For years, marketing teams across industries have turned to implementing traditional Customer Data Platforms (CDPs) as separate systems purpose-built to unlock growth with first-party data. Event Tracking : Capturing behavioral events such as page views, add-to-cart, signup, purchase, subscription, etc.

Data Warehouse 52

Data Warehouse Cloud Data Data Modeling Data Models 52

AWS Machine Learning Blog

MAY 8, 2024

This meticulous approach allows Dialog Axiata to gain valuable insights into customer behavior, enabling them to predict potential churn events with remarkable accuracy. Instead of directly ingesting data from the data warehouse, the required features for training and inference steps are taken from the feature store.

ML 126

ML ML AWS AI 126

AWS Machine Learning Blog

APRIL 4, 2024

We have built one of the largest databases of brand impressions in the world with over 6 billion data points. The analyst is given direct access to the raw data or through our data warehouse. He excels in building and deploying deep learning models to handle large-scale data efficiently.

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phData

DECEMBER 12, 2023

Snowflake’s built-for-the-cloud architecture is highly performant and designed to handle large volumes of data and data consumers. Because of its cloud architecture, users do not have to worry about the maintenance of the infrastructure and the database going down at an inopportune time.

Data Warehouse 52

Data Warehouse Machine Learning Machine Learning Tableau 52

phData

DECEMBER 4, 2024

Like most Gen AI use cases, the first step to achieving customer service automation is to clean and centralize all information in a data warehouse for your AI to work from. As with customer service automation, the main challenge is to have all your product manuals and documentation in a central database for the AI to process.

AI 52

AI Data Warehouse AI Data Quality 52

Alation

MARCH 1, 2022

Lineage helps them identify the source of bad data to fix the problem fast. Manual lineage will give ARC a fuller picture of how data was created between AWS S3 data lake, Snowflake cloud data warehouse and Tableau (and how it can be fixed). Time is money,” said Leonard Kwok, Senior Data Analyst, ARC.

Data Warehouse 52

Data Warehouse Data Lakes Cloud Data Database 52

phData

AUGUST 22, 2023

This post was co-written by Arnab Mondal and Ayush Kumar Singh Fivetran’s LDP, or Local Data Processing (which was previously known as HVR or High Volume Replicator), is a data replication tool that helps businesses move data from one data source to another. POWERPC-64BIT (AIX: 6.1, Linux (x86-64 bit) based on GLIBC 2.12

Database 52

Database Data Warehouse Cloud Data Analytics 52

phData

AUGUST 22, 2023

This post was co-written by Arnab Mondal and Ayush Kumar Singh Fivetran’s LDP, or Local Data Processing (which was previously known as HVR or High Volume Replicator), is a data replication tool that helps businesses move data from one data source to another. POWERPC-64BIT (AIX: 6.1, Linux (x86-64 bit) based on GLIBC 2.12

Database 52

Database Data Warehouse Cloud Data Analytics 52

Pickl AI

AUGUST 9, 2024

Velocity It indicates the speed at which data is generated and processed, necessitating real-time analytics capabilities. Businesses need to analyse data as it streams in to make timely decisions. This diversity requires flexible data processing and storage solutions. Once data is collected, it needs to be stored efficiently.

Big Data 52

Big Data Big Data Big Data Analytics Big Data Analytics 52

Pickl AI

JULY 30, 2024

Flow-Based Programming : NiFi employs a flow-based programming model, allowing users to create complex data flows using simple drag-and-drop operations. This visual representation simplifies the design and management of data pipelines. Guaranteed Delivery : NiFi ensures that data delivered reliably, even in the event of failures.

ETL 52

ETL Data Lakes Big Data Big Data 52

phData

SEPTEMBER 8, 2023

This ensures that BI applications can handle data growth without sacrificing performance or responsiveness. BI workloads can be dynamic, with varying demands depending on factors such as time of day, seasonality, or specific business events. Snowflake supports encryption at rest and in transit. Contact our Team of Snowflake Experts!

Business Intelligence 59

Business Intelligence Business Intelligence Database Data Warehouse 59

Pickl AI

AUGUST 11, 2024

These tables are called “factless fact tables” or “junction tables” They are used for modelling many-to-many relationships or for capturing timestamps of events. Dealing with Sparse Data In some cases, fact tables may contain a large number of null values due to missing data.

Data Quality 52

Data Quality Data Warehouse Data Governance Analytics 52

phData

FEBRUARY 5, 2024

Creating the databases, schemas, roles, and access grants that comprise a data system information architecture can be time-consuming and error-prone. Luckily phData has created a template-driven Provision Tool that automates onboarding users and projects to Snowflake, allowing your data teams to start producing real value immediately.

SQL 52

SQL Database Data Quality Data Warehouse 52

phData

JUNE 13, 2023

A data model typically consists of one or more data sources, which can be anything from Excel spreadsheets to cloud-based databases and one or more tables that represent the data in those sources. The relationships that connect these tables are the cornerstone of data modeling and the main topic of this blog.

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Power BI Data Models Data Modeling Data Warehouse 93