sala - Big data is a variety of tools, approaches and methods for processing both structured and unstructured data in order to use them for specific tasks and purposes.

kaver - To understand this, it is helpful to read the history. In 2001, Gartner proposed the following definition: Big data is a variety of data that comes in at an ever-increasing rate and is constantly growing in volume. Thus, the three main properties of big data are diversity, high speed of arrival, and high volume. In simple terms, big data is unusually large and complex datasets, usually from non-standard sources. The size of these datasets is so large that traditional processing programs cannot handle them. But big data can be used to solve business problems that previously seemed too complex. By the way, I recommend that you read the article The Pros and Cons of Big Data for Businesses https://idapgroup.com/blog/pros-and-cons-of-big-data-for-businesses/ . You will find a lot of useful information here. Separately, I want to note that the latest advances in technology have significantly reduced the cost of storage and computing, which makes it possible to store and process ever-growing amounts of data. Modern technologies allow you to store and process more data at a lower cost, which allows you to make more accurate and informed business decisions.

carol3 - The first step in enhancing data quality is data profiling, which is the first assessment of how disparate data sets are currently structured. The next step is data matching, which identifies matching pieces of information among big datasets. Data quality software https://provectus.com/ can also detect and correct variations in data. By using software that can automatically identify and correct differences, data quality assurance solutions can save time and money. Once you implement data quality assurance, your business can benefit from the latest data and analytics

carol3 - The first step in enhancing data quality is data profiling, which is the first assessment of how disparate data sets are currently structured. The next step is data matching, which identifies matching pieces of information among big datasets. Data quality software can also detect and correct variations in data. By using software https://provectus.com/ that can automatically identify and correct differences, data quality assurance solutions can save time and money. Once you implement data quality assurance, your business can benefit from the latest data and analytics