Data Monitoring - Revision history

User at 17:39, 15 March 2023

2023-03-15T17:39:59Z

User at 18:04, 12 January 2023

2023-01-12T18:04:25Z

User at 15:32, 26 October 2022

2022-10-26T15:32:38Z

User at 15:31, 26 October 2022

2022-10-26T15:31:23Z

User at 14:27, 17 October 2022

2022-10-17T14:27:08Z

User at 14:24, 17 October 2022

2022-10-17T14:24:38Z

User at 13:42, 17 October 2022

2022-10-17T13:42:19Z

User at 13:22, 17 October 2022

2022-10-17T13:22:00Z

User at 13:21, 17 October 2022

2022-10-17T13:21:11Z

User at 12:03, 17 October 2022

2022-10-17T12:03:11Z

@@ Line 1: / Line 1: @@
-===What is Data Monitoring?<ref>[https://toolkit.ncats.nih.gov/glossary/data-monitoring/ What is Data Monitoring?]</ref>===
+== What is Data Monitoring?<ref>[https://toolkit.ncats.nih.gov/glossary/data-monitoring/ What is Data Monitoring?]</ref> ==
 '''Data monitoring''' is the process of reviewing the information entered into the database for accuracy and completeness. The data can also be evaluated to ensure the entered information will accomplish the goals of the registry or clinical study. Data monitoring is performed proactively, either continuously or on a set schedule. The goal of data monitoring is to ensure high-quality data. Data monitoring can catch data that are inconsistent with other participants and therefore may need verification. It can also detect trends or patterns that differ from information collected in the past. Interventional clinical trials are most often monitored by a Data Monitoring Committee (DMC).
-===The Need for Data Monitoring'''<ref>[https://www.informatica.com/services-and-training/glossary-of-terms/data-monitoring-definition.html#:~:text=Data%20monitoring%20is%20a%20business,standards%20for%20formatting%20and%20consistency. Why perform data monitoring?]</ref>===
+== The Need for Data Monitoring'''<ref>[https://www.informatica.com/services-and-training/glossary-of-terms/data-monitoring-definition.html#:~:text=Data%20monitoring%20is%20a%20business,standards%20for%20formatting%20and%20consistency. Why perform data monitoring?]</ref> ==
 Data monitoring allows an organization to proactively maintain a high, consistent standard of data quality. By checking data routinely as it is stored within applications, organizations can avoid the resource-intensive pre-processing of data before it is moved. With data monitoring, data is quality checked at creation time rather than before a move.
-===Attributes of Data Monitoring'''<ref>[https://www.edq.com/glossary/data-monitoring/ What is data monitoring software?]</ref>===
+== Attributes of Data Monitoring<ref>[https://www.edq.com/glossary/data-monitoring/ What is data monitoring software?]</ref> ==
 Simply put, monitoring data is the act of having procedures, technologies, and benchmarks in place for tracking the quality and usefulness of data.
@@ Line 20: / Line 20: @@
-===The Importance of Data Monitoring<ref>[https://www.indeed.com/career-advice/career-development/data-monitoring Why is data monitoring important?]</ref>===
+== The Importance of Data Monitoring<ref>[https://www.indeed.com/career-advice/career-development/data-monitoring Why is data monitoring important?]</ref> ==
-Data monitoring is important because it helps preserve data integrity and usefulness. By ensuring high-quality data, a business can avoid multiplying ongoing problems with future data interpretation and analysis. Examples of potential problems with data include duplicated or missing data points, vague or indistinguishable data, inconsistent data and data drift.
+Data monitoring is important because it helps preserve data integrity and usefulness. By ensuring high-quality data, a business can avoid multiplying ongoing problems with future data interpretation and analysis. Examples of potential problems with data include duplicated or missing data points, vague or indistinguishable data, inconsistent data, and data drift.
-Data monitoring can help a business determine the source of data problems and identify solutions. Depending on how the organization uses its data, monitoring can help assure regulatory compliance, reduce costs or increase profitability, so regular monitoring and correcting data deficiencies is essential.
+Data monitoring can help a business determine the source of data problems and identify solutions. Depending on how the organization uses its data, monitoring can help assure regulatory compliance, reduce costs, or increase profitability, so regular monitoring and correcting data deficiencies is essential.
-===Elements of an Automated Data Monitoring System<ref>[https://medium.com/@vikati/the-rise-of-data-monitoring-7221eef63e7f Elements of an Automated Data Monitoring System]</ref>===
+== Elements of an Automated Data Monitoring System<ref>[https://medium.com/@vikati/the-rise-of-data-monitoring-7221eef63e7f Elements of an Automated Data Monitoring System]</ref> ==
 Given the importance of data, data monitoring capabilities in companies are generally below expectations. While large tech companies like Netflix and Uber have built sophisticated data-monitoring platforms and processes, many small and even large companies still can’t easily monitor their data. Enterprises often rely on their legacy data quality software that doesn’t map to their current data stack. Many startups scrape by with a combination of homegrown scripts and tools like Grafana and Prometheus.
@@ Line 40: / Line 40: @@
-===Methods of Data Monitoring<ref>[https://www.observe.ai/contact-center-glossary/what-is-data-monitoring What are the different methods of data monitoring?]</ref>===
+== Methods of Data Monitoring<ref>[https://www.observe.ai/contact-center-glossary/what-is-data-monitoring What are the different methods of data monitoring?]</ref> ==
 *Speech Analytics: This technique uses artificial intelligence (AI) to monitor calls in real-time to identify tone and sentiment, gauge customer emotion and satisfaction, and even use algorithms to study the skills of agents.
 *Text (Interaction) Analytics: Contact centers using chat, email, or social media to interact with customers have many data quality monitoring tools at their disposal. These can scan the text to identify and analyze data. Note: interaction analytics may include speech analytics as well.
@@ Line 47: / Line 47: @@
-===Data Monitoring Techniques<ref>[https://theecmconsultant.com/data-quality-monitoring/ What are the Available Data Quality Monitoring Techniques?]</ref>===
+== Data Monitoring Techniques<ref>[https://theecmconsultant.com/data-quality-monitoring/ What are the Available Data Quality Monitoring Techniques?]</ref> ==
 *Data-Driven Approach: this is when the process of analyzing the data and identifying areas that need improvement is done manually by human beings. This approach is time-consuming and it has high costs as well.
-*Data Analytics: This approach collects, analyzes, and reports on the performance of a business in real time. This approach has low cost but it can only be used for certain types of businesses such as manufacturing or retail companies.
+*Data Analytics: This approach collects, analyzes, and reports on the performance of a business in real-time. This approach has low cost but it can only be used for certain types of businesses such as manufacturing or retail companies.
 *Metrics-Based Approach: This approach uses metrics for assessing the performance of a business without having to do any manual analysis or reporting on the data. This approach is efficient and inexpensive.
-===Effective Data Monitoring<ref>[https://databand.ai/blog/data-monitoring-advice-for-when-things-absolutely-must-not-break/ Qualities of an effective data monitoring system]</ref>===
+== Effective Data Monitoring<ref>[https://databand.ai/blog/data-monitoring-advice-for-when-things-absolutely-must-not-break/ Qualities of an effective data monitoring system]</ref> ==
 For a data monitoring system to be useful, it must be:
 *Granular: it must indicate specifically where an issue is occurring, and with what code.
@@ Line 62: / Line 62: @@
-===Data Monitoring Tool Selection Criteria<ref>[https://www.comparitech.com/net-admin/best-database-monitoring-tools/  Methodology for selecting a database monitoring tool]</ref>===
+== Data Monitoring Tool Selection Criteria<ref>[https://www.comparitech.com/net-admin/best-database-monitoring-tools/  Methodology for selecting a database monitoring tool]</ref> ==
 The bigger the server, the more CPU and memory are needed to process the data. Using a database monitoring tool is the only reliable way to monitor databases. Similarly, the widespread use of SQL Servers has made monitoring SQL Servers a top priority for monitoring SQL server performance.
 Below is a methodology for analyzing and selecting a database monitoring tool based on the following criteria:
@@ Line 71: / Line 71: @@
 *An easy-to-use interface
 *Secure access procedures that include authentication and multiple user accounts
-*A free trial, demo, or money-back period for no-risk assessment
+*A free trial, demo, or money-back period for a no-risk assessment
 *A reasonable price that reflects the quality of the product and offers value for money
-====Data Monitoring Tools and Software====
+=== Data Monitoring Tools and Software ===
 Below is a list of some of the Data Monitoring Tools available in the market today:
 *SolarWinds Database Performance Analyzer for SQL Server: Includes real-time performance monitoring plus analysis functions. Runs on Windows Server.
@@ Line 82: / Line 82: @@
 *SolarWinds AppOptics APM: A comprehensive cloud-based application performance monitor that includes specialized processes for monitoring databases
 *Site24x7 Server Monitoring: An online monitoring package that includes SQL monitoring and analysis functions.
-*Paessler PRTG Network Monitor: Database monitoring functions are part of this all-in-one network, server, and applications monitor. Runs on Windows Server.
+*Paessler PRTG Network Monitor: Database monitoring functions are part of this all-in-one network, server, and applications monitoring. Runs on Windows Server.
 *SentryOne SQL Sentry: Live database performance monitoring with automated index defragmentation.
 *Atera: A remote management solution for managed service providers that includes database backup automation and supervision.
@@ Line 95: / Line 95: @@
-===Data Monitoring Committee<ref>[https://www.advarra.com/blog/dmc-vs-irb-whats-the-difference/ What Is an Independent Data Monitoring Committee (DMC)?]</ref>===
+== Data Monitoring Committee<ref>[https://www.advarra.com/blog/dmc-vs-irb-whats-the-difference/ What Is an Independent Data Monitoring Committee (DMC)?]</ref> ==
 A Data Monitoring Committee (DMC) is an independent group of experts that conduct a periodic review of accumulated interim data during a clinical trial. DMCs are strenuously recommended for certain clinical trials by both US FDA and EU EMA guidelines.
@@ Line 103: / Line 103: @@
-===Benefits of Data Monitoring'''<ref>[Benefits of Data Monitoring https://www.egnyte.com/guides/governance/data-monitoring]</ref>===
+== Benefits of Data Monitoring'''<ref>[https://www.egnyte.com/guides/governance/data-monitoring Benefits of Data Monitoring]</ref> ==
 *A holistic view of the data ecosystem is created and maintained, providing increased visibility.
 *Agility and speed are increased across an organization because data can be used immediately.
@@ Line 118: / Line 118: @@
-=== See Also ===
+== See Also ==
-<div style="column-count:2;-moz-column-count:4;-webkit-column-count:4">
+*[[Data]]
 == References ==
 <references />
 __NOTOC__

@@ Line 120: / Line 120: @@
 === See Also ===
 <div style="column-count:2;-moz-column-count:4;-webkit-column-count:4">
-*[[Data]]
 </div>

@@ Line 136: / Line 136: @@
 *[[Data Management]]
 *[[Data Mining]]
 *[[Data Munging]]
 *[[Data Portability]]

@@ Line 120: / Line 120: @@
 === See Also ===
 <div style="column-count:2;-moz-column-count:4;-webkit-column-count:4">
-[[Data Compatibility]]<br />
+*[[Data]]
-[[Data Access]]<br />
+*[[Data Access]]
-[[Data Analysis]]<br />
+*[[Data Analysis]]
-[[Data Analytics]]<br />
+*[[Data Analytics]]
-[[Data Architecture]]<br />
+*[[Data Architecture]]
-[[Data Asset Framework (DAF)]]<br />
+*[[Data Asset Framework (DAF)]]
-[[Data Buffer]]<br />
+*[[Data Buffer]]
-[[Data Center]]<br />
+*[[Data Center]]
-[[Data Center Infrastructure]]<br />
+*[[Data Center Infrastructure]]
-[[Data Center Infrastructure Management (DCIM)]]<br />
+*[[Data Center Infrastructure Management (DCIM)]]
-[[Data Cleansing]]<br />
+*[[Data Cleansing]]
-[[Big Data]]<br />
+*[[Data Compatibility]]
-[[Big Data Integration]]<br />
+*[[Data Governance]]
-[[Big Data Maturity Model (BDMM)]]<br />
+*[[Data Integration]]
-[[Metadata]]<br />
+*[[Data Management]]
-[[Data Collection]]<br />
+*[[Data Mining]]
-[[Data Compatibility]]<br />
+*[[Data Monitoring]]
-[[Data Consolidation]]<br />
+*[[Data Munging]]
-[[Data Deduplication]]<br />
+*[[Data Portability]]
-[[Data Delivery Platform (DDP)]]<br />
+*[[Data Quality]]
-[[Data Description (Definition) Language (DDL)]]<br />
+*[[Data Reference Model (DRM)]]
-[[Data Dictionary]]<br />
+*[[Data Security]]
-[[Data Discovery]]<br />
+*[[Data Transformation]]
-[[Data Driven Organization]]<br />
+*[[Data Visualization]]
-[[Data Element]]<br />
+*[[Data Warehouse]]
 </div>

@@ Line 20: / Line 20: @@
-===The Importance of Data Monitoring<ref>[https://www.indeed.com/career-advice/career-development/data-monitoring Why is data monitoring important?]===
+===The Importance of Data Monitoring<ref>[https://www.indeed.com/career-advice/career-development/data-monitoring Why is data monitoring important?]</ref>===
 Data monitoring is important because it helps preserve data integrity and usefulness. By ensuring high-quality data, a business can avoid multiplying ongoing problems with future data interpretation and analysis. Examples of potential problems with data include duplicated or missing data points, vague or indistinguishable data, inconsistent data and data drift.
@@ Line 95: / Line 95: @@
-===Data Monitoring Committee<ref>
+===Data Monitoring Committee<ref>[https://www.advarra.com/blog/dmc-vs-irb-whats-the-difference/ What Is an Independent Data Monitoring Committee (DMC)?]</ref>===
 A Data Monitoring Committee (DMC) is an independent group of experts that conduct a periodic review of accumulated interim data during a clinical trial. DMCs are strenuously recommended for certain clinical trials by both US FDA and EU EMA guidelines.

@@ Line 18: / Line 18: @@
 *Uniqueness
 Data quality monitoring helps you reveal problem areas where the most inaccuracies are observed, track unusual or abnormal behaviors, and identify where you should focus your data quality initiatives.
@@ Line 32: / Line 38: @@
 [[File:Data Monitoring Elements.png|500px|Elements of Data Monitoring]]<br />