GAVS Technology

AUGUST 31, 2021

Each interaction within the healthcare system generates critical patient data that needs to be available across hospitals, practices, or clinics. Consequently, the industry witnessed a surge in the amount of patient data collected and stored. The varying use of data standards can affect interoperability.

Healthcare 40

Healthcare Data Security Government Data Quality 40

Astera

APRIL 4, 2024

Data governance’s primary purpose is to ensure organizational data assets’ quality, integrity, security, and effective use. The key objectives of Data Governance include: Enhancing Clear Ownership: Assigning roles to ensure accountability and effective management of data assets.

Data Governance 52

Data Governance Government E-Commerce Data Quality 52

Astera

MAY 13, 2024

Consolidating, summarized data from wide-ranging sources ensures you aren’t considering just one perspective in your analysis. Performance Monitoring Data aggregation facilitates you in monitoring key performance indicators (KPIs) more effectively.

Supply Chain 52

Supply Chain E-Commerce Healthcare Data Quality 52

Astera

APRIL 24, 2024

A data governance framework is a structured way of managing and controlling the use of data in an organization. It helps establish policies, assign roles and responsibilities, and maintain data quality and security in compliance with relevant regulatory standards.

Data Governance 52

Data Governance Government Data Architecture Data Quality 52

Astera

MAY 8, 2024

All three have a unique purpose in organizing, defining, and accessing data assets within an organization. For instance, in a healthcare institution, “Patient Admission” might be “the process of formally registering a patient for treatment or care within the facility.”

Data Governance 52

Data Governance Government Healthcare Retail 52

Astera

APRIL 28, 2023

Data management can be a daunting task, requiring significant time and resources to collect, process, and analyze large volumes of information. Continuous Data Quality Monitoring According to Gartner , poor data quality cost enterprises an average of $15 million per year.

E-Commerce 40

E-Commerce Supply Chain Artificial Intelligence Data Warehouse 40

Astera

MAY 31, 2024

Here are the critical components of data science: Data Collection : Accumulating data from diverse sources like databases, APIs , and web scraping. Data Cleaning and Preprocessing : Ensuring data quality by managing missing values, eliminating duplicates, normalizing data, and preparing it for analysis.

Data Analytics 52

Data Analytics Data Analytics Data Warehouse Healthcare 52

Astera

MARCH 28, 2024

Data Catalog vs. Data Dictionary A common confusion arises when data dictionaries come into the discussion. Both data catalog and data dictionary serve essential roles in data management. How to Build a Data Catalog? Creating a catalog involves multiple important steps.

Data Governance 52

Data Governance Government Data Discovery Data Quality 52

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. For example, streaming data from sensors to an analytics platform where it is processed and visualized immediately.

IBM Maintenance 52

IBM Maintenance Data Warehouse IBM Support Real-time Data 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 Data Governance Business Intelligence 52

Astera

OCTOBER 26, 2023

The more data we generate, the more cleaning we must do. But what makes cleaning data so essential? Gartner reveals that poor data quality costs businesses $12.9 Data cleansing is critical for any organization that relies on accurate data. Interactive Data Profiling: Gain insights into your data visually.

Data Quality 52

Data Quality Healthcare Retail Visualization 52

Astera

MARCH 31, 2023

In today’s data-driven world, businesses rapidly generate massive amounts of data. Managing this data effectively and timely is critical for decision-making, but how can they make sense of all this data most efficiently? 2. Ensuring data quality Another major challenge is improving data quality.

Data Quality 52

Data Quality Data Security Data Warehouse Monitoring 52

Astera

JANUARY 24, 2024

Modern data management relies heavily on ETL (extract, transform, load) procedures to help collect, process, and deliver data into an organization’s data warehouse. However, ETL is not the only technology that helps an enterprise leverage its data. Considering cloud-first data management?

Data Warehouse 52

Data Warehouse Data Quality Data Management Data Security 52

Astera

APRIL 24, 2024

Business analysts, data scientists, IT professionals, and decision-makers across various industries rely on data aggregation tools to gather and analyze data. Essentially, any organization aiming to leverage data for competitive advantage will benefit from data aggregation tools.

IBM Support 52

IBM Support IBM Maintenance IBM cost E-Commerce 52

Astera

DECEMBER 7, 2023

IoT Data Processing : Handling and analyzing data from sensors or connected devices as it arrives. Real-time Analytics : Making immediate business decisions based on the most current data. Log Monitoring : Analyzing logs in real-time to identify issues or anomalies.

Supply Chain 52

Supply Chain E-Commerce Data Warehouse Real-time Data 52

Astera

DECEMBER 7, 2023

IoT Data Processing : Handling and analyzing data from sensors or connected devices as it arrives. Real-time Analytics : Making immediate business decisions based on the most current data. Log Monitoring : Analyzing logs in real-time to identify issues or anomalies.

Supply Chain 52

Supply Chain E-Commerce Real-time Data Data Warehouse 52

Astera

MARCH 11, 2024

According to a recent Gartner survey, 85% of enterprises now use cloud-based data warehouses like Snowflake for their analytics needs. Unsurprisingly, businesses are already adopting Snowflake ETL tools to streamline their data management processes.

Data Warehouse 52

Data Warehouse Documentation Monitoring Data Quality 52

Astera

OCTOBER 30, 2023

It allows you to cross-reference, refine, and weave together data from multiple sources to make a unified whole. Elevate Your Data Quality, Zero-Coding Required View Demo Data Enrichment Techniques So how does data enrichment really work? Monitor key performance indicators (KPIs) to gauge the impact.

E-Commerce 40

E-Commerce Talent Acquisition Healthcare Data Quality 40

Astera

MAY 6, 2024

Whether it’s choosing the right marketing strategy, pricing a product, or managing supply chains, data mining impacts businesses in various ways: Finance : Banks use predictive models to assess credit risk, detect fraudulent transactions, and optimize investment portfolios. Data quality is a priority for Astera.

Data Mining 52

Data Mining Supply Chain Data Quality Visualization 52

Smart Data Collective

JUNE 19, 2019

Aligning these elements of risk management with the handling of big data requires that you establish real-time monitoring controls. This technique applies across different industries, including healthcare, service, and manufacturing. Risk Management Applications for Analyzing Big Data.

Big Data 176

Big Data Logistics Monitoring Data Analytics 176

Astera

JANUARY 23, 2024

Data vault goes a step further by preserving data in its original, unaltered state, thereby safeguarding the integrity and quality of data. Additionally, it allows users to apply further data quality rules and validations in the information layer, guaranteeing that data is perfectly suited for reporting and analysis.

Agile 52

Agile Data Warehouse Data Quality Government 52

Astera

JUNE 13, 2023

Acting as a conduit for data, it enables efficient processing, transformation, and delivery to the desired location. By orchestrating these processes, data pipelines streamline data operations and enhance data quality. Stream processing platforms handle the continuous flow of data, enabling real-time insights.

E-Commerce 52

E-Commerce Data Quality Real-time Data Data Warehouse 52

Astera

FEBRUARY 14, 2024

Data Vault 101: Your Guide to Adaptable and Scalable Data Warehousing As businesses deal with larger and more diverse volumes of data, managing that data has become increasingly difficult. It applies selected business rules, calculations, data cleansing and data quality functions to the data.

Data Warehouse 52

Data Warehouse Data Modelling Agile Data Quality 52

Astera

SEPTEMBER 28, 2023

Data Quality: ETL facilitates data quality management , crucial for maintaining a high level of data integrity, which, in turn, is foundational for successful analytics and data-driven decision-making. ETL pipelines ensure that the data aligns with predefined business rules and quality standards.

Data Warehouse 52

Data Warehouse Data Quality E-Commerce Real-time Data 52

Data Pine

DECEMBER 4, 2019

With technologies such as natural language processing, machine learning, pattern recognition cognitive computing is considered as a next-generation system that will help experts to make better decisions throughout industries such as healthcare, retail, security, and e-commerce, among others. With the expected generated revenue of $13.8

Business Intelligence 84

Business Intelligence Business Intelligence IBM Support IBM Maintenance 84