Ajith S's articles What is data quality management? Data is the driving force of every organization in the modern world. As organizations continue to collect more and more data, the need to manage the quality of the data becomes more prominent each day. Data Quality Management can be defined as a set of practices undertaken by a data manager or a data organization […] January 9, 2024January 9, 2024 Saving Bookmark this article Bookmarked How to ensure data quality and integrity? Data has grown to become an organization’s most valuable asset. Not every data is valuable, but only data that can be trusted. If organizations work with untrustworthy data, it can easily result in wrong insights, skewed analysis, and incorrect decisions. Data quality and data integrity are two terms used to describe the condition of data. The […] December 12, 2023December 12, 2023 Saving Bookmark this article Bookmarked How do different personas in an organization see data quality? Data Engineers: We look into Data Engineering, which combines three core practices around Data Management, Software Engineering, and I&O. This focuses primarily on reconstituting data into usable consumer forms by building and operationalizing data pipelines across various data and analytics platforms. Data Engineers, aka producers of the data, must be robust across data modeling, pipeline […] June 12, 2023June 12, 2023 Saving Bookmark this article Bookmarked Modern Data Quality Approach An organization with 1000 employees, in 2022, has an average of 177 SaaS applications. Most of these applications store data relevant to their needs, However, in order to perform cross-organizational analysis, this data needs to be aggregated, enriched and integrated. This process vastly increases the scope of data quality initiative from the past days, when […] May 22, 2023May 22, 2023 Saving Bookmark this article Bookmarked Top 4 Benefits of Modern Data Quality The goal of a data quality program is to build trust in data. However, trust is an expansive, and often ill-defined term that can include many topics that control and manage data. Trusted data is possible when all the components of the metadata management platform work as a single unit. For example, without accurate data, […] May 16, 2023May 16, 2023 Saving Bookmark this article Bookmarked 4 Pillars of Modern Data Quality The need for high quality, trustworthy data in our world will never go away. Treating data quality as a technical problem and not a business problem may have been the biggest limiting factor in making progress. Finding technical defects, such as duplicate data, missing values, out of order sequences and drift from expected patterns of […] May 10, 2023May 10, 2023 Saving Bookmark this article Bookmarked What is trustable data? Why do you need it? Introduction The need to use predictive analysis and modeling in forecasting the growth of data has been brought about by how great the volume and variety of data there currently is. According to Gartner, “Data preparation is an iterative and agile process for exploring, combining, cleaning, and transforming raw data into curated datasets for self-service […] October 13, 2022October 13, 2022 Saving Bookmark this article Bookmarked Best practices to maintain high data quality Introduction With the world’s data multiplying in leaps and bounds, every organization is trying to make better business decisions in marketing, product development, and finance using insights from the data they hold. The value of businesses today can be measured by the quality of the data they hold. With this in mind, data has become […] October 7, 2022October 7, 2022 Saving Bookmark this article Bookmarked 10 steps to data profiling for successful data discovery: Part II In this article, we continue to the previous Part I – 10 steps to data profiling. Step 1 Ensure that the data selected for profiling meets the regulatory threshold. To achieve this, it is important to understand the regulations governing the target data. In some cases, organizations that own the data may not have the […] September 27, 2022September 27, 2022 Saving Bookmark this article Bookmarked Challenges and best practices of data cleansing This article will detail the challenges and the best practices of data cleansing in data quality management. Maintaining Data Accuracy Data accuracy is the biggest challenge encountered by many businesses in their quest to cleanse data. Having accurate data is the foundation of the usefulness of data in all its stages of use. Data develops […] September 13, 2022September 13, 2022 Saving Bookmark this article Bookmarked Challenges and best practices of data cleansing This article will detail the challenges and the best practices of data cleansing in data quality management. Maintaining Data Accuracy Data accuracy is the biggest challenge encountered by many businesses in their quest to cleanse data. Having accurate data is the foundation of the usefulness of data in all its stages of use. Data develops […] September 13, 2022September 13, 2022 Saving Bookmark this article Bookmarked Challenges and best practices of data cleansing This article will detail the challenges and the best practices of data cleansing in data quality management. Maintaining Data Accuracy Data accuracy is the biggest challenge encountered by many businesses in their quest to cleanse data. Having accurate data is the foundation of the usefulness of data in all its stages of use. Data develops […] September 13, 2022September 13, 2022 Saving Bookmark this article Bookmarked 10 steps to data profiling for successful data discovery: Part I Introduction Data profiling is where to start when data quality is a priority. This is the step that ensures that the data you have access to is legitimate and has acceptable quality. Data profiling focuses on examining and analyzing data, followed by the creation of a useful summary of that data. Effective data profiling falls into […] September 1, 2022September 1, 2022 Saving Bookmark this article Bookmarked Data Observability Vs Data Quality: What makes them different? Defining Data Observability and Data Quality As companies gather seemingly endless data streams from an increasing number of sources, they start to amass an ecosystem of data storage, would-be end-users, and pipelines. With each additional layer of complexity, opportunities for data downtime, moments when data is partial, erroneous, missing, or otherwise inaccurate, multiply. As a […] August 25, 2022August 25, 2022 Saving Bookmark this article Bookmarked Semantic Discovery for Data Quality Management Fundamentals of Semantic Discovery A data-driven business gains no value from its data which lacks a clear meaning and context. Such businesses will, therefore, constantly try to make sense of their massive data. How? Some businesses have teams of business analysts, data specialists, and other personnel employed to manually review, analyze, and classify all available […] August 22, 2022August 22, 2022 Saving Bookmark this article Bookmarked Data Observability Vs Data Quality: What makes them different? Defining Data Observability and Data Quality As companies gather seemingly endless data streams from an increasing number of sources, they start to amass an ecosystem of data storage, would-be end-users, and pipelines. With each additional layer of complexity, opportunities for data downtime, moments when data is partial, erroneous, missing, or otherwise inaccurate, multiply. As a […] July 7, 2022July 7, 2022 Saving Bookmark this article Bookmarked The Noise in Modern Data Quality The need for high-quality, trustworthy data in our world will never go away. With the growth in data, the need arises more than ever before. Even though we have evolved from data silos to pipelines (ELT/TL) to streaming to modern data stack/warehouse, multi-cloud, and data mesh — we are still faced with an age-old problem of […] June 8, 2022June 8, 2022 Saving Bookmark this article Bookmarked 4 Reasons why you need an augmented data integration tool Introduction We are in a time when information is the core element of business success for companies in almost any industry. As technologies emerge and find large-scale adoption, there is an influx of massive amounts of data within enterprises. Two primary challenges need to be solved to obtain the necessary information. First is trustable information […] May 6, 2022May 6, 2022 Saving Bookmark this article Bookmarked Data quality: What and why is it important? With the internet producing quintillions of readily available information per day, you could be forgiven to think that data is losing its value. Apparently, data is one of those weird commodities that go up in value the more they are available, or perhaps we haven’t produced enough to attain the demand-supply equilibrium. Virtually all companies […] April 26, 2022April 26, 2022 Saving Bookmark this article Bookmarked How AI and ML are transforming data quality management? Introduction In recent years technology has become prominent, both at work and at home. Machine learning (ML) and Artificial Intelligence (AI) are evolving quickly today. Almost everyone will have some interaction with a form of AI daily. Some common examples include Siri, Google Maps, Netflix, and Social media (Facebook/Snapchat).AI and ML have popularly used buzzwords […] April 20, 2022April 20, 2022 Saving Bookmark this article Bookmarked What is data quality management? Data is the driving force of every organization in the modern world. As organizations continue to collect more and more data, the need to manage the quality of the data becomes more prominent each day. Data Quality Management can be defined as a set of practices undertaken by a data manager or a data organization […] April 12, 2022April 12, 2022 Saving Bookmark this article Bookmarked What is Data Catalog? Importance, features and benefits A data catalog is defined as a neat and organized inventory of data assets across data sources in an organization. March 28, 2022March 28, 2022 Saving Bookmark this article Bookmarked Continuous Data Quality Monitoring with DQLabs In today’s world, we have been doing more of the traditional data management practices. This is a process of connecting people, processes, and technologies by creating governance foundations, going into data stewardship, standardizing and setting policies, execution of master data management, data quality, and with a feedback loop. The problem is that it takes a […] March 23, 2022March 23, 2022 Saving Bookmark this article Bookmarked
What is data quality management? Data is the driving force of every organization in the modern world. As organizations continue to collect more and more data, the need to manage the quality of the data becomes more prominent each day. Data Quality Management can be defined as a set of practices undertaken by a data manager or a data organization […] January 9, 2024January 9, 2024 Saving Bookmark this article Bookmarked
How to ensure data quality and integrity? Data has grown to become an organization’s most valuable asset. Not every data is valuable, but only data that can be trusted. If organizations work with untrustworthy data, it can easily result in wrong insights, skewed analysis, and incorrect decisions. Data quality and data integrity are two terms used to describe the condition of data. The […] December 12, 2023December 12, 2023 Saving Bookmark this article Bookmarked
How do different personas in an organization see data quality? Data Engineers: We look into Data Engineering, which combines three core practices around Data Management, Software Engineering, and I&O. This focuses primarily on reconstituting data into usable consumer forms by building and operationalizing data pipelines across various data and analytics platforms. Data Engineers, aka producers of the data, must be robust across data modeling, pipeline […] June 12, 2023June 12, 2023 Saving Bookmark this article Bookmarked
Modern Data Quality Approach An organization with 1000 employees, in 2022, has an average of 177 SaaS applications. Most of these applications store data relevant to their needs, However, in order to perform cross-organizational analysis, this data needs to be aggregated, enriched and integrated. This process vastly increases the scope of data quality initiative from the past days, when […] May 22, 2023May 22, 2023 Saving Bookmark this article Bookmarked
Top 4 Benefits of Modern Data Quality The goal of a data quality program is to build trust in data. However, trust is an expansive, and often ill-defined term that can include many topics that control and manage data. Trusted data is possible when all the components of the metadata management platform work as a single unit. For example, without accurate data, […] May 16, 2023May 16, 2023 Saving Bookmark this article Bookmarked
4 Pillars of Modern Data Quality The need for high quality, trustworthy data in our world will never go away. Treating data quality as a technical problem and not a business problem may have been the biggest limiting factor in making progress. Finding technical defects, such as duplicate data, missing values, out of order sequences and drift from expected patterns of […] May 10, 2023May 10, 2023 Saving Bookmark this article Bookmarked
What is trustable data? Why do you need it? Introduction The need to use predictive analysis and modeling in forecasting the growth of data has been brought about by how great the volume and variety of data there currently is. According to Gartner, “Data preparation is an iterative and agile process for exploring, combining, cleaning, and transforming raw data into curated datasets for self-service […] October 13, 2022October 13, 2022 Saving Bookmark this article Bookmarked
Best practices to maintain high data quality Introduction With the world’s data multiplying in leaps and bounds, every organization is trying to make better business decisions in marketing, product development, and finance using insights from the data they hold. The value of businesses today can be measured by the quality of the data they hold. With this in mind, data has become […] October 7, 2022October 7, 2022 Saving Bookmark this article Bookmarked
10 steps to data profiling for successful data discovery: Part II In this article, we continue to the previous Part I – 10 steps to data profiling. Step 1 Ensure that the data selected for profiling meets the regulatory threshold. To achieve this, it is important to understand the regulations governing the target data. In some cases, organizations that own the data may not have the […] September 27, 2022September 27, 2022 Saving Bookmark this article Bookmarked
Challenges and best practices of data cleansing This article will detail the challenges and the best practices of data cleansing in data quality management. Maintaining Data Accuracy Data accuracy is the biggest challenge encountered by many businesses in their quest to cleanse data. Having accurate data is the foundation of the usefulness of data in all its stages of use. Data develops […] September 13, 2022September 13, 2022 Saving Bookmark this article Bookmarked
Challenges and best practices of data cleansing This article will detail the challenges and the best practices of data cleansing in data quality management. Maintaining Data Accuracy Data accuracy is the biggest challenge encountered by many businesses in their quest to cleanse data. Having accurate data is the foundation of the usefulness of data in all its stages of use. Data develops […] September 13, 2022September 13, 2022 Saving Bookmark this article Bookmarked
Challenges and best practices of data cleansing This article will detail the challenges and the best practices of data cleansing in data quality management. Maintaining Data Accuracy Data accuracy is the biggest challenge encountered by many businesses in their quest to cleanse data. Having accurate data is the foundation of the usefulness of data in all its stages of use. Data develops […] September 13, 2022September 13, 2022 Saving Bookmark this article Bookmarked
10 steps to data profiling for successful data discovery: Part I Introduction Data profiling is where to start when data quality is a priority. This is the step that ensures that the data you have access to is legitimate and has acceptable quality. Data profiling focuses on examining and analyzing data, followed by the creation of a useful summary of that data. Effective data profiling falls into […] September 1, 2022September 1, 2022 Saving Bookmark this article Bookmarked
Data Observability Vs Data Quality: What makes them different? Defining Data Observability and Data Quality As companies gather seemingly endless data streams from an increasing number of sources, they start to amass an ecosystem of data storage, would-be end-users, and pipelines. With each additional layer of complexity, opportunities for data downtime, moments when data is partial, erroneous, missing, or otherwise inaccurate, multiply. As a […] August 25, 2022August 25, 2022 Saving Bookmark this article Bookmarked
Semantic Discovery for Data Quality Management Fundamentals of Semantic Discovery A data-driven business gains no value from its data which lacks a clear meaning and context. Such businesses will, therefore, constantly try to make sense of their massive data. How? Some businesses have teams of business analysts, data specialists, and other personnel employed to manually review, analyze, and classify all available […] August 22, 2022August 22, 2022 Saving Bookmark this article Bookmarked
Data Observability Vs Data Quality: What makes them different? Defining Data Observability and Data Quality As companies gather seemingly endless data streams from an increasing number of sources, they start to amass an ecosystem of data storage, would-be end-users, and pipelines. With each additional layer of complexity, opportunities for data downtime, moments when data is partial, erroneous, missing, or otherwise inaccurate, multiply. As a […] July 7, 2022July 7, 2022 Saving Bookmark this article Bookmarked
The Noise in Modern Data Quality The need for high-quality, trustworthy data in our world will never go away. With the growth in data, the need arises more than ever before. Even though we have evolved from data silos to pipelines (ELT/TL) to streaming to modern data stack/warehouse, multi-cloud, and data mesh — we are still faced with an age-old problem of […] June 8, 2022June 8, 2022 Saving Bookmark this article Bookmarked
4 Reasons why you need an augmented data integration tool Introduction We are in a time when information is the core element of business success for companies in almost any industry. As technologies emerge and find large-scale adoption, there is an influx of massive amounts of data within enterprises. Two primary challenges need to be solved to obtain the necessary information. First is trustable information […] May 6, 2022May 6, 2022 Saving Bookmark this article Bookmarked
Data quality: What and why is it important? With the internet producing quintillions of readily available information per day, you could be forgiven to think that data is losing its value. Apparently, data is one of those weird commodities that go up in value the more they are available, or perhaps we haven’t produced enough to attain the demand-supply equilibrium. Virtually all companies […] April 26, 2022April 26, 2022 Saving Bookmark this article Bookmarked
How AI and ML are transforming data quality management? Introduction In recent years technology has become prominent, both at work and at home. Machine learning (ML) and Artificial Intelligence (AI) are evolving quickly today. Almost everyone will have some interaction with a form of AI daily. Some common examples include Siri, Google Maps, Netflix, and Social media (Facebook/Snapchat).AI and ML have popularly used buzzwords […] April 20, 2022April 20, 2022 Saving Bookmark this article Bookmarked
What is data quality management? Data is the driving force of every organization in the modern world. As organizations continue to collect more and more data, the need to manage the quality of the data becomes more prominent each day. Data Quality Management can be defined as a set of practices undertaken by a data manager or a data organization […] April 12, 2022April 12, 2022 Saving Bookmark this article Bookmarked
What is Data Catalog? Importance, features and benefits A data catalog is defined as a neat and organized inventory of data assets across data sources in an organization. March 28, 2022March 28, 2022 Saving Bookmark this article Bookmarked
Continuous Data Quality Monitoring with DQLabs In today’s world, we have been doing more of the traditional data management practices. This is a process of connecting people, processes, and technologies by creating governance foundations, going into data stewardship, standardizing and setting policies, execution of master data management, data quality, and with a feedback loop. The problem is that it takes a […] March 23, 2022March 23, 2022 Saving Bookmark this article Bookmarked
