Smart Data Collective

SEPTEMBER 26, 2021

There’s not much value in holding on to raw data without putting it to good use, yet as the cost of storage continues to decrease, organizations find it useful to collect raw data for additional processing. The raw data can be fed into a database or data warehouse. The central concept is the idea of a document.

Database 130

Database Data Visualization Big Data Big Data 130

Smart Data Collective

JUNE 6, 2021

Other uses may include: Maintenance checks Guides, resources, training and tutorials (all available in BigQuery documentation ) Employee efficiency reviews Machine learning Innovation advancements through the examination of trends. (1). Big data analytics advantages. What is Big Data?” What is Google BigQuery? References.

Big Data Analytics 137

Big Data Analytics Big Data Analytics Big Data Big Data 137

Data Science 101

DECEMBER 3, 2019

Do you have a data governance document? What data do you collect? Technical Questions Before Starting a Data Strategy. How and where is your current data stored? What is the current data infrastructure? Do you have a data warehouse? Do you use any external data?

Data Warehouse 84

Data Warehouse Data Governance Business Intelligence Business Intelligence 84

Dataconomy

SEPTEMBER 4, 2023

Text analytics: Text analytics, also known as text mining, deals with unstructured text data, such as customer reviews, social media comments, or documents. It uses natural language processing (NLP) techniques to extract valuable insights from textual data. Poor data integration can lead to inaccurate insights.

Analytics 203

Analytics Analytics Big Data Analytics Big Data Analytics 203

Smart Data Collective

JULY 20, 2021

As a standalone product, this software helps professionals with rich sets of spreadsheets, charts and documents. Quip integration tool will allow teams to improve collaborations, export and import live data, enhanced visibility and outstanding device support. This tool will help you to sync and store data from multiple sources quickly.

Big Data 142

Big Data Big Data ETL Analytics 142

Towards AI

FEBRUARY 13, 2023

How to build a chatbot that answers questions about documentation and cites its sources The tutorial was initially hosted via a live stream on our Learn AI Discord. Three 5-minute reads/videos to keep you learning 1.How

AI 98

AI AI Data Warehouse Data Lakes 98

IBM Journey to AI blog

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

AI 110

AI AI Data Warehouse Machine Learning 110

Smart Data Collective

APRIL 29, 2020

The extraction of raw data, transforming to a suitable format for business needs, and loading into a data warehouse. Data transformation. This process helps to transform raw data into clean data that can be analysed and aggregated. Data analytics and visualisation. Microsoft Azure.

Data Warehouse 97

Data Warehouse SQL Azure ETL 97

AWS Machine Learning Blog

JUNE 7, 2023

Amazon Textract is a machine learning (ML) service that automatically extracts text, handwriting, and data from any document or image. Amazon Textract has a Tables feature within the AnalyzeDocument API that offers the ability to automatically extract tabular structures from any document.

Machine Learning 96

Machine Learning Machine Learning Data Analysis Data Analysis 96

IBM Data Science in Practice

JANUARY 13, 2025

The blog post explains how the Internal Cloud Analytics team leveraged cloud resources like Code-Engine to improve, refine, and scale the data pipelines. Background One of the Analytics teams tasks is to load data from multiple sources and unify it into a data warehouse.

ETL 100

ETL Data Pipeline Database Data Warehouse 100

phData

MARCH 8, 2023

Examples of data sources and destinations include: Shopify Google Analytics Snowflake Data Cloud Oracle Salesforce Fivetran’s mission is to, “make access to data as easy as electricity” – so for the last 10 years, they have developed their platform into a leader in the cloud-based ELT market. What is Fivetran Used For?

Data Warehouse 96

Data Warehouse Data Engineering Data Engineer Data Engineering 96

Pickl AI

OCTOBER 17, 2024

Introduction ETL plays a crucial role in Data Management. This process enables organisations to gather data from various sources, transform it into a usable format, and load it into data warehouses or databases for analysis. Loading The transformed data is loaded into the target destination, such as a data warehouse.

ETL 52

ETL Data Warehouse Data Quality Data Governance 52

Smart Data Collective

APRIL 15, 2021

You need to make sure that all departments are data-friendly and in sync with each other. Most will include documentation of data sources, the KPIs of the specific industry, the kind of reporting necessary, and whether or not the data flow will require automation. Set Up Data Integration. Develop a Strategy.

Business Intelligence 107

Business Intelligence Business Intelligence Analytics Analytics 107

phData

NOVEMBER 4, 2024

For our hypothetical car company, we will use Dataiku’s Answers application to create a personalized customer service chatbot that can pull data from warranty contracts, car spec manuals, and customer history to respond to inquiries. Dataiku and Snowflake: A Good Combo?

Machine Learning 69

Machine Learning Machine Learning Data Science ML 69

Pickl AI

APRIL 9, 2025

By 2025, global data volumes are expected to reach 181 zettabytes, according to IDC. To harness this data effectively, businesses rely on ETL (Extract, Transform, Load) tools to extract, transform, and load data into centralized systems like data warehouses.

ETL 52

ETL Data Warehouse AWS Business Intelligence 52

AWS Machine Learning Blog

OCTOBER 9, 2024

To start using OpenSearch for anomaly detection you first must index your data into OpenSearch , from there you can enable anomaly detection in OpenSearch Dashboards. To learn more, see the documentation. To learn more, see the documentation. To learn more, see the documentation.

AWS 94

AWS ML ML Data Quality 94

phData

MARCH 7, 2023

This SDK allows you to directly connect to your Snowflake Data Warehouse and create a mapping of values and rows that need to be inserted. Once this step is complete, you can then insert the data. So how does Snowflake do this? Snowflake provides a Streaming Ingest SDK that you can implement using Java.

Data Warehouse 98

Data Warehouse Database 98

IBM Journey to AI blog

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.

AI 88

AI AI Data Warehouse ML 88

Alation

JANUARY 17, 2023

The modern data stack is a combination of various software tools used to collect, process, and store data on a well-integrated cloud-based data platform. 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 Warehouse 52

Data Warehouse ETL Tableau Cloud Data 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

ODSC - Open Data Science

FEBRUARY 24, 2023

Great Expectations GitHub | Website Great Expectations (GX) helps data teams build a shared understanding of their data through quality testing, documentation, and profiling. With Great Expectations , data teams can express what they “expect” from their data using simple assertions.

Exploratory Data Analysis 126

Exploratory Data Analysis Data Visualization Data Analysis Data Analysis 126

AWS Machine Learning Blog

FEBRUARY 14, 2024

Amazon Redshift has announced a feature called Amazon Redshift ML that makes it straightforward for data analysts and database developers to create, train, and apply machine learning (ML) models using familiar SQL commands in Redshift data warehouses.

AWS 140

AWS AI AI Database 140

phData

NOVEMBER 28, 2024

“ Vector Databases are completely different from your cloud data warehouse.” – You might have heard that statement if you are involved in creating vector embeddings for your RAG-based Gen AI applications. When documents are split into smaller chunks, search systems can find relevant sections more precisely and quickly.

Python 52

Python Database SQL Machine Learning 52

phData

SEPTEMBER 19, 2023

By incorporating metadata into the data model, users can easily discover, understand, and interpret the data stored in the lake. With the amounts of data involved, this can be crucial to utilizing a data lake effectively. However, this can be time-consuming and prone to human error, leading to misinformation.

Data Lakes 52

Data Lakes Data Modeling Data Models Data Warehouse 52

Smart Data Collective

JUNE 7, 2019

Volume – Companies gather data from different sources such as business transactions, social media, and other relevant data. Variety – It means all data can be presented in a variety of formats – from structured numeric data to the unstructured ones, which include text documents, audio, video, and email.

Big Data 104

Big Data Big Data Data Analysis Data Analysis 104

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. Document Search Everyone who’s ever read a product manual knows it can be notoriously complex, and finding the information you’re looking for is difficult.

AI 52

AI AI Data Warehouse Data Quality 52

AWS Machine Learning Blog

SEPTEMBER 18, 2024

Additionally, Feast promotes feature reuse, so the time spent on data preparation is reduced greatly. It promotes a disciplined approach to data modeling, making it easier to ensure data quality and consistency across the ML pipelines.

AWS 121

AWS Machine Learning Machine Learning ML 121

phData

JULY 18, 2023

With the birth of cloud data warehouses, data applications, and generative AI , processing large volumes of data faster and cheaper is more approachable and desired than ever. First up, let’s dive into the foundation of every Modern Data Stack, a cloud-based data warehouse.

Data Warehouse 52

Data Warehouse Analytics Analytics Cloud Data 52

phData

OCTOBER 12, 2022

Hosted Doc Site for Documentation One of the most powerful features of dbt can be the documentation you generate. This documentation can give different users insight into where data came from, what the profile of the data is, what the SQL looked like, and the DAG to know where the data is being used.

SQL 52

SQL Data Warehouse Data Visualization Cloud Data 52

Alation

AUGUST 4, 2022

“File-based storage of data is the norm even under more relational models. [In In the cloud], Graph databases, document stores, file stores, relational stores all now exist, each addressing different challenges.” In this way, the cloud has democratized access to some of the best outputs of big data.

Big Data 95

Big Data Big Data Apache Kafka Data Lakes 95

Smart Data Collective

FEBRUARY 20, 2022

In addition, well-known products boast a lot of implementations and use cases that are comprehensively reflected in the documentation. Another direction in the progress of database monitoring systems is the interoperability with so-called data warehouses, which are increasingly popular among corporate customers.

Database 130

Database Machine Learning Machine Learning Data Warehouse 130

phData

NOVEMBER 28, 2023

How to Get Started with Matillion Data Productivity Cloud That looks unbelievable, but trust me, you can get started with Matillion Data Productivity Cloud from 0 to start your first job in around 5 minutes. Creating Your Account First things first, let’s create your Matillion account in order to deploy your Data Productivity Cloud.

Data Warehouse 52

Data Warehouse Data Pipeline ETL Azure 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. She is passionate about data-driven AI and the area of depth in machine learning.

Clustering 94

Clustering AWS ML ML 94

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

IBM Journey to AI blog

JULY 17, 2023

These encoder-only architecture models are fast and effective for many enterprise NLP tasks, such as classifying customer feedback and extracting information from large documents. While they require task-specific labeled data for fine tuning, they also offer clients the best cost performance trade-off for non-generative use cases.

AI 74

AI AI Machine Learning Machine Learning 74

phData

SEPTEMBER 15, 2023

Salesforce Sync Out is a crucial tool that enables businesses to transfer data from their Salesforce platform to external systems like Snowflake, AWS S3, and Azure ADLS. Warehouse for loading the data (start with XSMALL or SMALL warehouses). See the Salesforce documentation for more information. Click Next.

Data Warehouse 52

Data Warehouse Tableau Data Silos Analytics 52

phData

APRIL 29, 2024

Oracle – The Oracle connector, a database-type connector, enables real-time data transfer of large volumes of data from on-premises or cloud sources to the destination of choice, such as a cloud data lake or data warehouse. File – Fivetran offers several options to sync files to your destination.

SQL 52

SQL Data Warehouse Azure Cloud Data 52