article thumbnail

Understanding Structured and Unstructured Data

Sisense

In our modern digital world, proper use of data can play a huge role in a business’s success. Datasets are exploding at an ever-accelerating rate, so collecting and analyzing data to maximum effect is crucial. Companies and businesses focus a lot on data collection in order to make sure they can get valuable insights out of it.

article thumbnail

8 data strategy mistakes to avoid

CIO Business Intelligence

“Similar to disaster recovery, business continuity, and information security, data strategy needs to be well thought out and defined to inform the rest, while providing a foundation from which to build a strong business.” Overlooking these data resources is a big mistake. Overlooking these data resources is a big mistake.

Insiders

Sign Up for our Newsletter

This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.

article thumbnail

What is a data scientist? A key data analytics role and a lucrative career

CIO Business Intelligence

What is a data scientist? Data scientists are analytical data experts who use data science to discover insights from massive amounts of structured and unstructured data to help shape or meet specific business needs and goals. Semi-structured data falls between the two.

article thumbnail

5 Applications for Corporate Text Analytics

Smart Data Collective

Text mining and text analysis are relatively recent additions to the data science world, but they already have an incredible impact on the corporate world. As businesses collect increasing amounts of often unstructured data, these techniques enable them to efficiently turn the information they store into relevant, actionable resources.

Analytics 120
article thumbnail

Seven Benefits of Using AI to Perform Text Analysis

Smart Data Collective

Considering the amount of unstructured data produced daily, NLP has become integral to efficiently understanding and analyzing text—based data. Moreover, the data collected is not free from error or biases if humans handle it. Unstructured data can be difficult to skim through.

article thumbnail

Data science vs data analytics: Unpacking the differences

IBM Big Data Hub

Data science is an area of expertise that combines many disciplines such as mathematics, computer science, software engineering and statistics. It focuses on data collection and management of large-scale structured and unstructured data for various academic and business applications.

article thumbnail

5 Hardware Accelerators Every Data Scientist Should Leverage

Smart Data Collective

Although SageMaker has become a popular hardware accelerator since it was launched in 2017, there are plenty of other overlooked hardware accelerators on the market. If you want to streamline various parts of the data science development process, then you should be aware of all of your options. However, it does have some downsides.