Astera

APRIL 7, 2023

In the world of medical services, large volumes of healthcare data are generated every day. Currently, around 30% of the world’s data is produced by the healthcare industry and this percentage is expected to reach 35% by 2025. The sheer amount of health-related data presents countless opportunities.

Data Warehouse 52

Data Warehouse Healthcare Data Management Data Quality 52

Astera

FEBRUARY 20, 2023

Healthcare data integration is a critical component of modern healthcare systems. Combining data from disparate sources, such as EHRs and medical devices, allow providers to gain a complete picture of patient health and streamline workflows. This data is mostly available in a structured format and easily accessible.

Healthcare 52

Healthcare Data Warehouse Data Mining Data Quality 52

Astera

APRIL 3, 2023

Data entry in healthcare is extremely common for one major reason: the number of documents – patient information, medical records, insurance forms, billing forms, lab reports, prescriptions, consent forms, medical charts, and that’s just the beginning. For the same reason, it is also vital that data is entered in a timely manner.

Healthcare 52

Healthcare Documentation Data Quality Planning 52

Astera

AUGUST 11, 2023

Healthcare organizations deal with huge amounts of data every day, from patient records and claims to lab results and prescriptions. However, not all data is created equal. Different systems and formats can make data exchange difficult, costly, and error-prone. What Does EDI Stand for in Healthcare?

Healthcare 52

Healthcare Documentation Planning Data Security 52

Astera

DECEMBER 2, 2022

What is Healthcare Data Migration? With 30% of world’s data volume produced from the medical industry, most healthcare organizations are using a data migration strategy to migrate their healthcare data from their on-premise legacy systems to advanced storage solutions. Some of those reasons are: 1.

Healthcare 52

Healthcare Documentation Data Quality Data Architecture 52

Dataversity

JANUARY 26, 2024

Data has famously been referred to as the “new oil,” powering the fifth industrial revolution. As our reliance on data-intensive sectors like finance, healthcare, and the Internet of Things (IoT) grows, the question of trust becomes paramount.

Digital 355

Digital Healthcare Finance Data Governance 355

The Data Administration Newsletter

MAY 2, 2023

Over the past few decades, data has been gaining significant importance. The uncontrollable spread of data around the world has forced data to become an essential component for various industries, including the healthcare sector. This is encouraging […]

Healthcare 52

Healthcare Data Quality Data Management 52

Analysts Corner

DECEMBER 21, 2022

As per Allied Market Research, by 2025 , the market for big data analytics in healthcare might reach $67.82 According to Healthcare Big Data Analytics Market Report 2022 , by 2027, big data in healthcare is predicted to reach $71.6 It is estimated to reach $16 billion by 2025 and $20 billion by 2026.

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Big Data Healthcare Data Quality Data Analytics 246

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

Smart Data Collective

SEPTEMBER 28, 2022

Big data management increases the reliability of your data. Big data management has many benefits. One of the most important is that it helps to increase the reliability of your data. Data quality issues can arise from a variety of sources, including: Duplicate records Missing records Incorrect data.

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Big Data Data Management Data Quality Healthcare 265

Astera

MAY 13, 2024

Government: Using regional and administrative level demographic data to guide decision-making. Healthcare: Reviewing patient data by medical condition/diagnosis, department, and hospital. Besides being relevant, your data must be complete, up-to-date, and accurate.

Supply Chain 52

Supply Chain E-Commerce Healthcare Data Quality 52

Analysts Corner

OCTOBER 31, 2023

Healthcare : sharing patient records and examination histories. Commercial : Customer Relationship Management (CRM) systems that integrate customer data and preferences to identify greater business opportunities in personalized campaigns and actions. Banking sector : integrating credit information, accounts, and financial transactions.

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Astera

FEBRUARY 27, 2024

A medical insurance claim is a bill that healthcare providers submit to the patient’s healthcare insurance company after they receive treatment or care. Medical Bills Medical bills are the invoices or statements healthcare providers issue after providing care.

Healthcare 52

Healthcare Documentation Pharmaceutical Data Quality 52

Smart Data Collective

SEPTEMBER 22, 2021

For example, businesses have used information derived from unstructured data to improve safety, advance healthcare outcomes, and automate business facilities based on worker insights – but let’s take a closer look. One type of unstructured data common in the healthcare industry is imaging, whether that’s a CT, MRI, or an X-ray.

Pharmaceutical 287

Pharmaceutical Healthcare Documentation Retail 287

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 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

Business Analysis Knowledge Share

NOVEMBER 10, 2023

Data cleaning and transformation In another scenario, you have received a messy dataset with missing values and inconsistent formatting. ChatGPT can help clean and transform the data by automatically filling in missing values, standardizing formats, and ensuring data quality. Q2: Can ChatGPT create interactive dashboards?

Data Analytics 66

Data Analytics Data Analytics Healthcare E-Commerce 66

Astera

MAY 11, 2023

Artificial Intelligence and RWE The transformative effect of Artificial Intelligence (AI) on RWE in healthcare is undeniable. By using AI in RWD analysis, policymakers can better understand the impact of different interventions and make informed decisions about healthcare spending.

Healthcare 40

Healthcare Artificial Intelligence Pharmaceutical Data Quality 40

Astera

JANUARY 23, 2023

The healthcare industry has evolved tremendously over the past few decades — with technological innovations facilitating its development. Billion by 2026 , showing the crucial role of health data management in the industry. and administrative data (insurance claims, billing details, etc.) trillion in 2020, making it 19.7

Data Management 52

Data Management IBM Maintenance Healthcare IBM cost 52

Astera

MAY 25, 2023

This would ensure that you can efficiently extract unstructured or semi-structured data from the medical records of any healthcare chain. Implementing Data Quality Rules for Reliable Extraction Accurate data extraction in health insurance can yield numerous benefits for you.

Healthcare 40

Healthcare Documentation Data Quality Customer Experience 40

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

OCTOBER 24, 2023

Data scientists commit nearly 80% of their time to data preparation, but only 3% of company data fulfills basic data quality standards. This highlights the critical importance of investing in data quality and efficient data preparation processes; they form the foundation for successful machine learning projects.

Data Quality 40

Data Quality Supply Chain Healthcare Real-time Data 40

Astera

JANUARY 12, 2024

It ensures that data from different departments, like patient records, lab results, and billing, can be securely collected and accessed when needed. Selecting the right data architecture depends on the specific needs of a business. Use Cases Choosing between a Data Vault and a Data Mesh often depends on specific use cases.

Data Architecture 52

Data Architecture Data Warehouse Data Quality Government 52

Astera

APRIL 28, 2023

For example, GE Healthcare leverage AI-powered data cleansing tools to improve the quality of data in its electronic medical records, reducing the risk of errors in patient diagnosis and treatment. Predictions As artificial intelligence continues to rapidly advance, its potential applications are constantly expanding.

E-Commerce 40

E-Commerce Supply Chain Artificial Intelligence Data Warehouse 40

Astera

MAY 9, 2023

These algorithms can identify patterns in data and use machine learning (ML) models to learn and adapt to new data sources. The perfect application of this would be in industries such as healthcare, where medical images such as X-rays and MRIs contain important diagnostic information.

Healthcare 40

Healthcare Retail Finance Data Quality 40

Business Analysis Knowledge Share

OCTOBER 27, 2023

Enhanced Data Governance : Use Case Analysis promotes data governance by highlighting the importance of data quality , accuracy, and security in the context of specific use cases. The data collected should be integrated into a centralized repository, often referred to as a data warehouse or data lake.

Business Intelligence 52

Business Intelligence Business Intelligence Supply Chain Data Governance 52

Astera

MARCH 28, 2024

It facilitates data discovery and exploration by enabling users to easily search and explore available data assets. Additionally, data catalogs include features such as data lineage tracking and governance capabilities to ensure data quality and compliance.

Data Governance 52

Data Governance Government Data Discovery Data Quality 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

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

FEBRUARY 2, 2024

Healthcare Forms: Patient intake forms, medical history forms, and insurance claims in healthcare involve a lot of unstructured data. Form processing extracts patient details, medical history, and insurance information to improve the efficiency of healthcare processes.

Healthcare 52

Healthcare Documentation Banking Data Quality 52

Astera

FEBRUARY 15, 2024

Data Extraction Data extraction s oftware obtains pertinent information from the form or document using techniques such as PDF document parsing, data querying, reusable pattern-based extraction templates , AI- based algorithms, natural language processing (NLP ) and Optic al Character Recognition (OCR).

Documentation 52

Documentation Healthcare Government Finance 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? AI-powered auto mapper to easily map your data from sources to destinations.

E-Commerce 40

E-Commerce Talent Acquisition Healthcare Data Quality 40

Astera

MARCH 30, 2023

Incompatible Data Formats : Different teams and departments might be storing data in different structures and formats. This makes it difficult to integrate and consolidate data from various departments, resulting in issues with data quality and delays in data processing.

Data Quality 52

Data Quality Data Warehouse Data Security Finance 52

Astera

MARCH 31, 2023

Consolidating data from these many sources is a formidable challenge on its own, and this is precisely where an automated data integration platform can help. 2. Ensuring data quality Another major challenge is improving data quality.

Data Quality 52

Data Quality Data Security Data Warehouse Monitoring 52

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

FEBRUARY 19, 2024

For example, intelligent form extraction can structure the data extracted from a contract into a table that shows the parties, terms, dates, and amounts involved. Intelligent form data extraction employs AI to enhance data quality. It can also add metadata, such as the source, format, and location of the contract.

Supply Chain 40

Supply Chain Documentation Banking Healthcare 40

GAVS Technology

SEPTEMBER 2, 2021

Unstructured big data continues to play a big role in enterprise insights. However, even more, important is to augment the big data processing with more meaningful data is subject to data quality rules, constraints and de-duplicated in the form of Master data.

Master Data Management 52

Master Data Management Healthcare Big Data Data Mining 52