Dell Technologies Channel Chats – Unstructured Data
Posted: Mon Dec 23, 2024 9:08 am
We're back with Dell Technologies Channel Chats interviews.
Today, César Tapias, together with Nacho Martín, explains why it is necessary for today's companies to store unstructured data correctly.
Before we go directly to the interview , let's do a quick recap of what unstructured data is.
What is unstructured data?
Unstructured data is generally binary data with no recognizable internal how to get usa phone number structure. It is a large, unorganized complex of various objects that has no value until it is identified and stored in an organized manner.
Once organized, the elements that make up the content can be searched and sorted (at least to some extent) to obtain information.
For example, although most data mining tools cannot analyze the information contained in emails (regardless of their organizational nature), collecting and classifying the data contained in them can show us relevant information about the organization.
This example illustrates the importance and scale that unstructured data can have.
What kind of unstructured data can we find?
Unstructured Data Types
Unstructured data is raw, unorganized data. Ideally, all of this information can be transformed into structured data.
Similarly, not all types of unstructured data can be easily converted into structured models. For example, take the example of email: the email contains information such as the time of sending, the person sending it, and the sender. However, the content of the message is not easily divided or categorized, and this can be a compatibility issue with the relational database system structure. Here is a limited list of unstructured data types:
E-mail.
Word processor file.
PDF files.
Spreadsheets.
Digital image.
Videos.
Audio.
Social media posts.
Unstructured Data Storage
Faced with the explosive growth of unstructured data, organizations of all sizes are looking for ways to effectively and cost-effectively store data while unlocking the valuable insights and intelligence it contains. Unstructured data, as we’ve discussed above, is essentially anything without a structured database—everything from emails, images, and documents to videos, social media content, and application-related data (such as logs).
Finding a solution to manage unstructured data is challenging. Next-generation applications that can handle rapidly growing unstructured data typically require the excellent performance of all-flash storage, but budget constraints make it difficult for organizations to afford the new capital and operational expenses required for these systems.
Dell Isilon provides a powerful, scale-out file storage solution that no matter how much unstructured data your environment needs to manage, it's easy to expand and use.
The challenge of unstructured data
While it is easy to query or report on structured data in relational databases, it is very difficult to extract value from unstructured data. A simple content search on text data may return interesting insights, but the depth and breadth of traditional structured content analysis does not help.
However, unstructured data accounts for approximately 80% of an organization's entire data set, and the amount of unstructured data tends to double every year.
Unstructured data accounts for approximately 80% of an organization's entire data set
Share
To harness the value of unstructured data and use it as a competitive advantage, organizations need tools to perform more complex and comprehensive analysis of these unique data sets, and artificial intelligence (AI) provides some answers.
Artificial intelligence tools have become extremely useful in analyzing the meaning of text and classifying it accurately, and machines can filter through thousands or millions of records faster than humans.
Artificial intelligence can assess tone and emotion in text content and use predictive models to predict possible outcomes. However, the operation and management of AI and deep learning (DL) technologies requires storage solutions with massive parallel file I/O, and traditional solutions cannot keep up.
As the number of concurrent computing threads increases, bottlenecks will become an issue because storage performance will suffer and CPU and GPU utilization without data will be greatly reduced.
We leave you the complete interview in this link between Nacho Martín, Channel Director of Dell Technologies and César Tapia, Director of the Unstructured Data Division of Dell Technologies, where they tell us a little more about the importance of these data.
Today, César Tapias, together with Nacho Martín, explains why it is necessary for today's companies to store unstructured data correctly.
Before we go directly to the interview , let's do a quick recap of what unstructured data is.
What is unstructured data?
Unstructured data is generally binary data with no recognizable internal how to get usa phone number structure. It is a large, unorganized complex of various objects that has no value until it is identified and stored in an organized manner.
Once organized, the elements that make up the content can be searched and sorted (at least to some extent) to obtain information.
For example, although most data mining tools cannot analyze the information contained in emails (regardless of their organizational nature), collecting and classifying the data contained in them can show us relevant information about the organization.
This example illustrates the importance and scale that unstructured data can have.
What kind of unstructured data can we find?
Unstructured Data Types
Unstructured data is raw, unorganized data. Ideally, all of this information can be transformed into structured data.
Similarly, not all types of unstructured data can be easily converted into structured models. For example, take the example of email: the email contains information such as the time of sending, the person sending it, and the sender. However, the content of the message is not easily divided or categorized, and this can be a compatibility issue with the relational database system structure. Here is a limited list of unstructured data types:
E-mail.
Word processor file.
PDF files.
Spreadsheets.
Digital image.
Videos.
Audio.
Social media posts.
Unstructured Data Storage
Faced with the explosive growth of unstructured data, organizations of all sizes are looking for ways to effectively and cost-effectively store data while unlocking the valuable insights and intelligence it contains. Unstructured data, as we’ve discussed above, is essentially anything without a structured database—everything from emails, images, and documents to videos, social media content, and application-related data (such as logs).
Finding a solution to manage unstructured data is challenging. Next-generation applications that can handle rapidly growing unstructured data typically require the excellent performance of all-flash storage, but budget constraints make it difficult for organizations to afford the new capital and operational expenses required for these systems.
Dell Isilon provides a powerful, scale-out file storage solution that no matter how much unstructured data your environment needs to manage, it's easy to expand and use.
The challenge of unstructured data
While it is easy to query or report on structured data in relational databases, it is very difficult to extract value from unstructured data. A simple content search on text data may return interesting insights, but the depth and breadth of traditional structured content analysis does not help.
However, unstructured data accounts for approximately 80% of an organization's entire data set, and the amount of unstructured data tends to double every year.
Unstructured data accounts for approximately 80% of an organization's entire data set
Share
To harness the value of unstructured data and use it as a competitive advantage, organizations need tools to perform more complex and comprehensive analysis of these unique data sets, and artificial intelligence (AI) provides some answers.
Artificial intelligence tools have become extremely useful in analyzing the meaning of text and classifying it accurately, and machines can filter through thousands or millions of records faster than humans.
Artificial intelligence can assess tone and emotion in text content and use predictive models to predict possible outcomes. However, the operation and management of AI and deep learning (DL) technologies requires storage solutions with massive parallel file I/O, and traditional solutions cannot keep up.
As the number of concurrent computing threads increases, bottlenecks will become an issue because storage performance will suffer and CPU and GPU utilization without data will be greatly reduced.
We leave you the complete interview in this link between Nacho Martín, Channel Director of Dell Technologies and César Tapia, Director of the Unstructured Data Division of Dell Technologies, where they tell us a little more about the importance of these data.