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 243

Business Intelligence Business Intelligence Data Warehouse Documentation 243

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 Management 220

Data Management Data Warehouse Master Data Management Digital Transformation 220

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.

Monitoring 313

Monitoring E-Commerce Data Warehouse Data Security 313

Astera

JUNE 14, 2023

What is Document Data Extraction? Document data extraction refers to the process of extracting relevant information from various types of documents, whether digital or in print. The process enables businesses to unlock valuable information hidden within unstructured documents.

Documentation 52

Documentation Supply Chain Healthcare Logistics 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 208

Big Data Real-time Data Data Warehouse Innovation 208

Sisense

APRIL 9, 2021

Until then though, they don’t necessarily want to spend the time and resources necessary to create a schema to house this data in a traditional data warehouse. Instead, businesses are increasingly turning to data lakes to store massive amounts of unstructured data. The rise of data warehouses and data lakes.

Data Warehouse 52

Data Warehouse Documentation Innovation Agile 52

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 Data Architecture Planning Big Data 78

Astera

FEBRUARY 28, 2024

52% of IT experts consider faster analytics essential to data warehouse success. However, scaling your data warehouse and optimizing performance becomes more difficult as data volume grows. Leveraging data warehouse best practices can help you design, build, and manage data warehouses more effectively.

Data Warehouse 52

Data Warehouse Cloud Computing Data Quality Monitoring 52

BizAcuity

APRIL 1, 2023

So to achieve the benefits of consolidation, Company B’s billing system must be integrated into Company A’s billing system which can be easily done by Informatica Informatica tool for Data Warehousing: Companies establishing their warehouses of data will need ETL to transfer the data to the warehouse from the Production system.

Data Warehouse 130

Data Warehouse Government Documentation Monitoring 130

Analysts Corner

JUNE 18, 2023

ETL Developer: Defining the Role An ETL developer is a professional responsible for designing, implementing, and managing ETL processes that extract, transform, and load data from various sources into a target data store, such as a data warehouse. Oracle, SQL Server, MySQL) Experience with ETL tools and technologies (e.g.,

Data Warehouse 130

Data Warehouse Data Quality Documentation Data Governance 130

ElegantJ BI

JANUARY 7, 2016

Information and data come from every corner of the enterprise, and can include databases, data warehouses, best-of-breed systems, legacy systems, and specialized systems like ERP, HR, Finance, Accounting , Warehousing and others.

Business Intelligence 130

Business Intelligence Business Intelligence Finance Data Warehouse 130

Analysts Corner

AUGUST 13, 2023

The Process of Data Profiling The data profiling process typically involves the following steps: 1. Data Collection: The first step is to gather data from various sources. This could include databases, data warehouses, file systems, or external data feeds.

Data Quality 130

Data Quality Data Warehouse Data Discovery Innovation 130

Astera

OCTOBER 27, 2023

What is a Cloud Data Warehouse? Simply put, a cloud data warehouse is a data warehouse that exists in the cloud environment, capable of combining exabytes of data from multiple sources. A cloud data warehouse is critical to make quick, data-driven decisions.

Data Warehouse 52

Data Warehouse Data Quality Big Data Predictive Analytics 52

Astera

DECEMBER 29, 2023

Among the key players in this domain is Microsoft, with its extensive line of products and services, including SQL Server data warehouse. In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Astera

DECEMBER 29, 2023

Among the key players in this domain is Microsoft, with its extensive line of products and services, including SQL Server data warehouse. In this article, we’re going to talk about Microsoft’s SQL Server-based data warehouse in detail, but first, let’s quickly get the basics out of the way.

Data Warehouse 52

Data Warehouse Data Management Data Modelling Data Quality 52

Sisense

JULY 8, 2020

Dealing with Data is your window into the ways Data Teams are tackling the challenges of this new world to help their companies and their customers thrive. In recent years we’ve seen data become vastly more available to businesses. This has allowed companies to become more and more data driven in all areas of their business.

Data Warehouse 90

Data Warehouse Embedded Analytics Real-time Data Documentation 90

Whizlabs

JUNE 27, 2021

Describing the components of a modern data warehouse. Describing data processing and data ingestion over Azure. Describing data visualization over Microsoft Power BI. How to Prepare for the Microsoft Azure Data Fundamentals DP-900 Exam? Step 2: Check the Microsoft Documentations.

Documentation 104

Documentation Data Warehouse Data Visualization Data Analytics 104

Actian

JULY 31, 2019

Primarily, Relational DataBase Management Systems (RDBMS) managed the needs of these systems and eventually evolved into data warehouses, storing and administering Online Analytical Processing (OLAP) for historical data analysis from various companies, such as Teradata, IBM, SAP, and Oracle.

IBM Support 8

IBM Support Documentation IBM Maintenance Data Warehouse 8

Domo

MAY 7, 2021

.” Here’s a shortlist of dark data and the common places it lives: Documents. The same goes for Word documents, forms, PDFs, and presentations. Data repositories. Lots of data—structured and unstructured—gets dumped into data warehouses, lakes, and non-relational databases.

Data Warehouse 98

Data Warehouse Documentation Retail Finance 98

BizAcuity

DECEMBER 28, 2022

Informatica tool for Data Warehousing: Companies establishing their warehouses of data will need ETL to transfer the data to the warehouse from the Production system. Typical actions required in data warehouses are: Data warehouses put information from many sources together for analysis.

Data Warehouse 100

Data Warehouse Government Documentation Monitoring 100

Smart Data Collective

JANUARY 22, 2020

Small companies value the ability to store documents in the cloud and conveniently manage them. Large business players appreciate the opportunity to save money on the acquisition and maintenance of their own data storage infrastructure. In recent years, cloud computing has gained increasing popularity and proved its effectiveness.

Cloud Computing 152

Cloud Computing Data Security Data Warehouse Documentation 152

Business Analysis Knowledge Share

OCTOBER 24, 2023

Data Warehousing is the process of collecting, storing, and managing data from various sources into a central repository. This repository, often referred to as a data warehouse , is specifically designed for query and analysis. Data Sources Data Warehouses collect data from diverse sources within an organization.

IBM Maintenance 75

IBM Maintenance Data Warehouse IBM cost Data Quality 75

ElegantJ BI

JANUARY 7, 2016

Information and data come from every corner of the enterprise, and can include databases, data warehouses, best-of-breed systems, legacy systems, and specialized systems like ERP, HR, Finance, Accounting , Warehousing and others.

Business Intelligence 100

Business Intelligence Business Intelligence Finance Data Warehouse 100

ElegantJ BI

JANUARY 7, 2016

Information and data come from every corner of the enterprise, and can include databases, data warehouses, best-of-breed systems, legacy systems, and specialized systems like ERP, HR, Finance, Accounting , Warehousing and others.

Business Intelligence 100

Business Intelligence Business Intelligence Finance Data Warehouse 100

Astera

SEPTEMBER 25, 2024

It provides many features for data integration and ETL. While Airbyte is a reputable tool, it lacks certain key features, such as built-in transformations and good documentation. Limited documentation: Many third-party reviews mention Airbyte lacks adequate connector-related documentation. Govern their data assets.

Real-time Data 52

Real-time Data Data Warehouse Documentation Monitoring 52

Sisense

JULY 22, 2020

They hold structured data from relational databases (rows and columns), semi-structured data ( CSV , logs, XML , JSON ), unstructured data (emails, documents, PDFs), and binary data (images, audio , video). Sisense provides instant access to your cloud data warehouses. Connect tables.

Digital Transformation 98

Digital Transformation Data Warehouse IBM Support IBM cost 98

Sisense

JULY 2, 2020

Many popular cloud analysis tools, including Sisense for Cloud Data Teams, support both on-premise database servers and cloud data warehouses. When companies use cloud applications (for example, Salesforce) they need to get that data from the cloud and into their databases for analysis.

Documentation 98

Documentation Data Warehouse Planning 98

Astera

DECEMBER 28, 2023

Airbyte vs Fivetran vs Astera: Overview Airbyte Finally, Airbyte is primarily an open-source data replication solution that leverages ELT to replicate data between applications, APIs, data warehouses, and data lakes. Like other data integration platforms , Airbyte features a visual UI with built-in connectors.

Data Warehouse 52

Data Warehouse Data Quality Documentation Data Management 52

Astera

DECEMBER 28, 2023

Airbyte vs Fivetran vs Astera: Overview Airbyte Finally, Airbyte is primarily an open-source data replication solution that leverages ELT to replicate data between applications, APIs, data warehouses, and data lakes. Like other data integration platforms , Airbyte features a visual UI with built-in connectors.

Data Warehouse 52

Data Warehouse Data Quality Documentation Data Management 52

Astera

FEBRUARY 26, 2024

Azure SQL Data Warehouse, now called Azure Synapse Analytics, is a powerful analytics and BI platform that enables organizations to process and analyze large volumes of data in a centralized place. However, this data is often scattered across different systems, making it difficult to consolidate and utilize effectively.

Data Warehouse 52

Data Warehouse Data Quality Real-time Data Documentation 52

Astera

APRIL 9, 2023

Data extraction is a crucial part of any business dealing with large volumes of information and involves capturing data from various sources, such as invoices, receipts, contracts, and other documents. That’s where AI-powered data extraction with reusable template-based extraction comes in.

Documentation 52

Documentation Healthcare Banking Finance 52

Astera

MARCH 11, 2024

It eliminates the need for complex infrastructure management, resulting in streamlined operations. According to a recent Gartner survey, 85% of enterprises now use cloud-based data warehouses like Snowflake for their analytics needs. What are Snowflake ETL Tools? Snowflake ETL tools are not a specific category of ETL tools.

Data Warehouse 52

Data Warehouse Documentation Monitoring Data Quality 52

Sisense

MARCH 20, 2019

MongoDB (or NoSQL) : An open source Database Management System (DBMS), MongoDB uses a document-oriented database model. That means that instead of using tables in rows in a database, MongoDB is made up of collections of documents. Get ready data engineers, now you need to have both AWS and Microsoft Azure to be considered up-to-date.

Big Data 72

Big Data IBM Maintenance IBM Support Data Warehouse 72

Astera

DECEMBER 16, 2022

John Stillwagen, Senior Director MIS at La Jolla Institute for Immunology, demonstrated how efficiently our data warehouse solution, Astera Data Warehouse Builder, helps you build an enterprise-grade data warehouse via a no-code interface. Astera Data Stack version 10.0 Learn more about version 10.0

Data Warehouse 59

Data Warehouse Big Data Data Management Documentation 59

Astera

DECEMBER 9, 2024

However, managing, analyzing, and governing the data is a complex process. While some use cases are more optimistic than others, intelligent document processing (IDP) is one of the most practical applications of GenAI, with a near-instant return on investment and a universal appeal for enterprises from all sectors.

Data Warehouse 52

Data Warehouse Data Governance Government Data Quality 52

Astera

APRIL 24, 2024

There are different types of data ingestion tools, each catering to the specific aspect of data handling. Standalone Data Ingestion Tools : These focus on efficiently capturing and delivering data to target systems like data lakes and data warehouses.

Data Warehouse 52

Data Warehouse Real-time Data Documentation Data Quality 52

Sisense

APRIL 7, 2020

In addition, this data lives in so many places that it can be hard to derive meaningful insights from it all. This is where analytics and data platforms come in: these systems, especially cloud-native Sisense, pull in data from wherever it’s stored ( Google BigQuery data warehouse , Snowflake , Redshift , etc.).

Big Data 86

Big Data Data Warehouse Product Management Product Management 86