Astera

FEBRUARY 27, 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 Data Quality Cloud Computing Monitoring 52

Data Pine

OCTOBER 25, 2022

7) “Data Science For Business: What You Need To Know About Data Mining And Data-Analytic Thinking” by Foster Provost & Tom Fawcett. Don’t be deceived by the advanced data mining topics covered in the book – we guarantee that it will teach you a host of practical skills.

Business Intelligence 117

Business Intelligence Business Intelligence Big Data Data Mining 117

Business Analysis Knowledge Share

MARCH 15, 2023

Let’s understand what a Data warehouse is and talk through some key concepts Datawarehouse Concepts for Business Analysis Data warehousing is a process of collecting, storing and managing data from various sources to support business decision making. What is Data Warehousing?

Big Data 52

Big Data Data Analytics Data Analytics Data Warehouse 52

Astera

NOVEMBER 27, 2023

Clean and accurate data is the foundation of an organization’s decision-making processes. However, studies reveal that only 3% of the data in an organization meets basic data quality standards, making it necessary to prepare data effectively before analysis. This is where data profiling comes into play.

Data Mining 52

Data Mining Data Quality Business Intelligence Business Intelligence 52

Data Pine

SEPTEMBER 27, 2022

One of the best beginners’ books on SQL for the analytical mindset, this masterful creation demonstrates how to leverage the two most vital tools for data query and analysis – SQL and Excel – to perform comprehensive data analysis without the need for a sophisticated and expensive data mining tool or application.

IBM cost 117

IBM cost Data Warehouse Business Intelligence Business Intelligence 117

Astera

JANUARY 23, 2024

Businesses need scalable, agile, and accurate data to derive business intelligence (BI) and make informed decisions. Their data architecture should be able to handle growing data volumes and user demands, deliver insights swiftly and iteratively. The combination of data vault and information marts solves this problem.

Agile 52

Agile Data Warehouse Data Quality Government 52

Data Pine

JANUARY 24, 2021

This can include a multitude of processes, like data profiling, data quality management, or data cleaning, but we will focus on tips and questions to ask when analyzing data to gain the most cost-effective solution for an effective business strategy. 4) How can you ensure data quality?

Data Visualization 126

Data Visualization Data Analytics Data Analytics Data Quality 126

Astera

FEBRUARY 20, 2023

A single source of truth allows healthcare organizations to apply data mining techniques to effectively detect and prevent fraud. Data Integration Challenges in Healthcare Healthcare data wields enormous power, but the sheer volume and variety of this data pose various challenges.

Healthcare 52

Healthcare Data Warehouse Data Mining Data Quality 52

Astera

DECEMBER 21, 2022

Data Extraction vs. Data Mining. People often confuse data extraction and data mining. The process of data extraction deals with extracting important information from sources, such as emails, PDF documents, forms, text files, social media, and images with the help of content extraction tools.

Data Mining 52

Data Mining Documentation Data Quality Data Warehouse 52

Astera

MAY 30, 2024

With today’s technology, data analytics can go beyond traditional analysis, incorporating artificial intelligence (AI) and machine learning (ML) algorithms that help process information faster than manual methods. Data analytics has several components: Data Aggregation : Collecting data from various sources.

Data Analytics 52

Data Analytics Data Analytics Data Mining Supply Chain 52

GAVS Technology

JUNE 2, 2021

While focus on API management helps with data sharing, this functionality has to be enhanced further as data sharing also needs to take care of privacy and other data governance needs. Data Lakes. A data lake is a centralized repository that allows you to store all your structured and unstructured data at any scale.

Healthcare 52

Healthcare Data Governance Government Data Mining 52

Astera

DECEMBER 22, 2022

Migrating data to the cloud is part of a flexible and scalable approach to data storage. Online data warehouses offer many benefits, such as connectivity to multiple unstructured data sources, faster analysis, and smoother disaster recovery. A robust data integration tool simplifies connecting to cloud storage.

Data Quality 52

Data Quality Data Mining Data Warehouse Data Governance 52

The BAWorld

NOVEMBER 22, 2021

Completeness is a data quality dimension and measures the existence of required data attributes in the source in data analytics terms, checks that the data includes what is expected and nothing is missing. Consistency is a data quality dimension and tells us how reliable the data is in data analytics terms.

Data Analytics 98

Data Analytics Data Analytics Data Warehouse Data Modelling 98

Data Pine

AUGUST 29, 2022

An excerpt from a rave review : “I would definitely recommend this book to everyone interested in learning about data from scratch and would say it is the finest resource available among all other Big Data Analytics books.”. If we had to pick one book for an absolute newbie to the field of Data Science to read, it would be this one.

Big Data 105

Big Data Data Analytics Data Analytics Data Mining 105

Astera

AUGUST 28, 2024

SAS Viya SAS Viya is an AI-powered, in-memory analytics engine that offers data visualization, reporting, and analytics for businesses. Users get simplified data access and integration from various sources with data quality tools and data lineage tracking built into the platform.

IBM Support 40

IBM Support IBM Maintenance IBM cost Data Mining 40

Insight Software

MAY 9, 2024

The key components of a data pipeline are typically: Data Sources : The origin of the data, such as a relational database , data warehouse, data lake , file, API, or other data store. This can include tasks such as data ingestion, cleansing, filtering, aggregation, or standardization.

IBM Maintenance 52

IBM Maintenance Data Warehouse IBM Support Real-time Data 52