Rocket-Powered Data Science

JULY 7, 2019

7) Security (airports, shopping malls, entertainment & sport events). Autonomous Vehicles: Self-driving (guided without a human), informed by data streaming from many sensors (cameras, radar, LIDAR), and makes decisions and actions based on computer vision algorithms (ML and AI models for people, things, traffic signs,…).

Internet of Things 157

Internet of Things Machine Learning Manufacturing IoT 157

Occam's Razor

SEPTEMBER 15, 2014

Dive into Mobile Reporting and Analysis. Dive into Mobile Reporting and Analysis. You would get the cool and sexy events, timers, rules and triggers, cross-domain tracking and all that. Dive into Mobile Reporting and Analysis. What do you learn from this report? What do you learn from this report?

Metrics 141

Metrics Reporting Analytics Marketing 141

datapine

NOVEMBER 27, 2019

The development of business intelligence to analyze and extract value from the countless sources of data that we gather at a high scale, brought alongside a bunch of errors and low-quality reports: the disparity of data sources and data types added some more complexity to the data integration process.

Business Intelligence 361

Business Intelligence Analytics Prescriptive Analytics Data Quality 361

Jet Global

JUNE 29, 2020

High-level methods and tools project future trends, behaviors, and events, giving organizations the ability to put together “what-if” models and calculations in effort to future-proof aspects of their operations. No need to be a developer or call IT to create your reports. Reports are easy to update with a single mouse click.

Analytics 98

Analytics Reporting Cost-Benefit Data mining 98

Sisense

MAY 11, 2021

Let’s say you want to subject a dataset to some form of anomaly detection; your model might take the form of a singular event stream that can be read by an anomaly detection service. Maybe one of the most common applications of a data model is for internal analysis and reporting through a BI tool. Enriching (e.g., Dig into AI.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Octopai

APRIL 19, 2021

Without organized metadata management, the validity of a company’s data is compromised and they won’t achieve adequate compliance, data governance, or generate correct insights. Additionally, the BI team will have trouble pinpointing the cause of errors, leading to inaccurate reports. Dataconomy.

Metadata 52

Metadata Management Business Intelligence Data Governance 52

BizAcuity

APRIL 28, 2019

According to a Federal Bank report, more than $600 billion of household debt in the U.S. Today, it’s no secret that most forward-thinking businesses are keenly following the latest developments on big data, artificial intelligence, machine learning, and predictive analytics. is delinquent as of June 30th, 2017.

Predictive Analytics 98

Predictive Analytics Analytics Big Data Data mining 98

CIO Business Intelligence

MAY 12, 2022

Predictive analytics tools blend artificial intelligence and business reporting. SPSS Modeler is a drag-and-drop tool for creating data pipelines that lead to actionable insights. The tool builds heavily on business intelligence and reporting by treating predictions as just another column in the analytics presentation.

Predictive Analytics 137

Predictive Analytics Analytics Statistics Machine Learning 137

Jet Global

MAY 9, 2024

A data pipeline is a series of processes that move raw data from one or more sources to one or more destinations, often transforming and processing the data along the way. Data pipelines support data science and business intelligence projects by providing data engineers with high-quality, consistent, and easily accessible data.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

CIO Business Intelligence

MARCH 24, 2023

Varonis Data Governance Suite Varonis’s solution automates data protection and management tasks leveraging a scalable Metadata Framework that enables organizations to manage data access, view audit trails of every file and email event, identify data ownership across different business units, and find and classify sensitive data and documents.

Data Governance 142

Data Governance Management Metadata Data Quality 142

AWS Big Data

FEBRUARY 22, 2023

Before implementing a data lake on AWS, Ruparupa had no infrastructure capable of processing the volume and variety of data formats in a short time. Data had to be manually processed by data analysts, and data mining took a long time. Because of the fast growth of data, it took 1–1.5

Data Lake 52

Data Lake Dashboards Cost-Benefit Metadata 52

Cloudera

NOVEMBER 30, 2017

They hold a series of well-attended industry events that focus advancing the art of modern analytics and big data. They have empowered countless companies to move beyond legacy reporting practices to lean, agile analytics practices. Big data platforms enable organizations to assemble data for a 360-degree view.

Strategy 40

Strategy Big Data Data mining Visualization 40

Sisense

APRIL 26, 2020

Key points to keep in mind about semi-structured data: Falls under the heading of unstructured data, but it has some lower-degree organization (still falls short of relational databases) Can be coerced into useful and easy-to-leverage table formats Examples of semi-structured data include XML, JSON, Emails, NoSQL DBs, event tracking, and web pages.

Unstructured Data 52

Unstructured Data Data Warehouse Structured Data Data mining 52

Jet Global

MAY 1, 2023

But many companies fail to achieve this goal because they struggle to provide the reporting and analytics users have come to expect. that gathers data from many sources. These tools prep that data for analysis and then provide reporting on it from a central viewpoint. These reports are critical to making decisions.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52