CIO Business Intelligence

APRIL 22, 2022

For more details on data science bootcamps, see “ 15 best data science bootcamps for boosting your career.”. Data science certifications. Organizations need data scientists and analysts with expertise in techniques for analyzing data. Data science teams. Data science is generally a team discipline.

Data Science 140

Data Science Statistics Machine Learning Visualization 140

IBM Big Data Hub

JULY 6, 2023

While data science and machine learning are related, they are very different fields. In a nutshell, data science brings structure to big data while machine learning focuses on learning from the data itself. What is data science? It’s also necessary to understand data cleaning and processing techniques.

Machine Learning 61

Machine Learning Data Science Statistics Deep Learning 61

IBM Big Data Hub

SEPTEMBER 19, 2023

To pursue a data science career, you need a deep understanding and expansive knowledge of machine learning and AI. And you should have experience working with big data platforms such as Hadoop or Apache Spark. Your skill set should include the ability to write in the programming languages Python, SAS, R and Scala.

Data Science 86

Data Science Data Analytics Prescriptive Analytics Analytics 86

BizAcuity

MARCH 18, 2019

Predictive analytics continues to gain popularity, and research proves that there is a gradual move toward credit scoring strategies developed using data mining and predictive analytics.

Predictive Analytics 83

Predictive Analytics Analytics Cost-Benefit Data mining 83

IBM Big Data Hub

AUGUST 28, 2023

One of the best ways to take advantage of social media data is to implement text-mining programs that streamline the process. What is text mining? In the age of big data, companies are always on the hunt for advanced tools and techniques to extract insights from data reserves.

Data mining 60

Data mining Machine Learning Deep Learning Marketing 60

IBM Big Data Hub

AUGUST 14, 2023

Advanced analytics help detect known and unknown threats to drive consistent and faster investigations every time and empower your security analysts to make data-driven decisions. With ML analytics models, your organization can gain additional insight into user behavior with predictive modeling and baselines of what is normal for a user.

Cost-Benefit 62

Cost-Benefit Machine Learning Consulting Data mining 62

Sisense

APRIL 10, 2020

These libraries are used for data collection, analysis, data mining, visualizations, and ML modeling. Nowadays text data is huge, so Deep Learning also comes into the picture. There are also a wide array of libraries available for both languages for text processing, text analysis, and text modeling.

Deep Learning 98

Deep Learning Data Science Machine Learning Visualization 98

Smart Data Collective

SEPTEMBER 26, 2021

Data is processed to generate information, which can be later used for creating better business strategies and increasing the company’s competitive edge. Working with massive structured and unstructured data sets can turn out to be complicated. So, let’s have a close look at some of the best strategies to work with large data sets.

Metadata 99

Metadata Visualization Unstructured Data Data mining 99

Rocket-Powered Data Science

JULY 6, 2021

Customer purchase patterns, supply chain, inventory, and logistics represent just a few domains where we see new and emergent behaviors, responses, and outcomes represented in our data and in our predictive models.

Data-driven 279

Data-driven Machine Learning IoT Deep Learning 279

datapine

NOVEMBER 27, 2019

Accordingly, predictive and prescriptive analytics are by far the most discussed business analytics trends among the BI professionals, especially since big data is becoming the main focus of analytics processes that are being leveraged not just by big enterprises, but small and medium-sized businesses alike.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Jet Global

MAY 9, 2024

Machine Learning Pipelines : These pipelines support the entire lifecycle of a machine learning model, including data ingestion , data preprocessing, model training, evaluation, and deployment. API Data Pipelines : These pipelines retrieve data from various APIs and load it into a database or application for further use.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

MAY 1, 2023

Users Want to Help Themselves Data mining is no longer confined to the research department. Today, every professional has the power to be a “data expert.” Ideally, your primary data source should belong in this group. Bid Goodbye to Standalone Users don’t want to have to leave their app or call IT for insights.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52