FineReport

APRIL 9, 2024

One of the key aspects of the role of BI platforms is their ability to streamline the process of data analysis and decision-making. They offer functionalities that allow for the integration and transformation of raw data into meaningful and actionable insights.

Business Intelligence 52

Business Intelligence Software Data-driven Predictive Modeling 52

Sisense

SEPTEMBER 3, 2020

Programming and statistics are two fundamental technical skills for data analysts, as well as data wrangling and data visualization. Data analysts in one organization might be called data scientists or statisticians in another. See an example: Explore Dashboard.

Statistics 97

Statistics Metrics Visualization Finance 97

Cloudera

JUNE 29, 2023

Implementing a modern data architecture makes it possible for financial institutions to break down legacy data silos, simplifying data management, governance, and integration — and driving down costs. Enhance counterparty risk assessment. Use ML to more realistically model and simulate stress scenarios.

Data Architecture 85

Data Architecture Risk Management Risk Management 85

DataRobot Blog

JULY 21, 2022

Data scientists need to understand the business problem and the project scope to assess feasibility, set expectations, define metrics, and design project blueprints. If there is no forward-looking predictive component to the use case, it can probably be addressed with analytics and visualizations applied to historical data.

Machine Learning 98

Machine Learning Metrics Modeling Testing 98

IBM Big Data Hub

DECEMBER 4, 2023

Clearly define the objective of the implementation project and determine its scope, timeline and budget as well as create a risk management plan. This is also the time to determine which data will be migrated, as some older data may be best stored in a secure archive.

Testing 79

Testing Consulting Digital Transformation Cost-Benefit 79

datapine

AUGUST 29, 2022

Whether you are a complete novice or a seasoned BI professional, you will find here some books on data analytics that will help you cultivate your understanding of this essential field. Before we delve deeper into the best books for data analytics, here are three big data insights to put their relevance and importance into perspective.

Big Data 263

Big Data Data Analytics Analytics Data mining 263

DataRobot Blog

DECEMBER 20, 2022

You can understand the data and model’s behavior at any time. Once you use a training dataset, and after the Exploratory Data Analysis, DataRobot flags any data quality issues and, if significant issues are spotlighted, will automatically handle them in the modeling stage. Rapid Modeling with DataRobot AutoML.

Management 59

Management Machine Learning Optimization Modeling 59