CIO Business Intelligence

APRIL 19, 2022

In any market segment you care to look at, you will find that the market front-runners will be those that have an exceptionally good data mining capability. Data that is accurate and easily accessible gives organisations the traction they need to target customers and deliver information or engagement without delay.

Digital Transformation 57

Digital Transformation Data mining Strategy Insurance 57

BizAcuity

APRIL 1, 2023

Data governance and security measures are critical components of data strategy. KPI Analysis: the process of evaluating the performance of an organization using a set of measurable metrics infrastructure: refers to the hardware, software, and other key resources that are used to manage, maintain and analyze data within an organization.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

BizAcuity

JANUARY 31, 2023

Data governance and security measures are critical components of data strategy. KPI Analysis: the process of evaluating the performance of an organization using a set of measurable metrics infrastructure: refers to the hardware, software, and other key resources that are used to manage, maintain and analyze data within an organization.

Business Intelligence 52

Business Intelligence Consulting KPI Data Warehouse 52

datapine

JULY 24, 2019

Data has never been more readily accessible. Approaches to communication are changing, and success in today’s technology-driven world correlates directly to the quantity rather than the quality of one’s information—metrics relating to the business, the client, the competitor, and the market. 3) Design data to avoid clutter.

Dashboards 148

Dashboards Business Intelligence Visualization KPI 148

IBM Big Data Hub

JULY 6, 2023

Other challenges include communicating results to non-technical stakeholders, ensuring data security, enabling efficient collaboration between data scientists and data engineers, and determining appropriate key performance indicator (KPI) metrics. Some people worry that AI and machine learning will eliminate jobs.

Machine Learning 56

Machine Learning Data Science Statistics Deep Learning 56

Domino Data Lab

MAY 20, 2021

Further, imbalanced data exacerbates problems arising from the curse of dimensionality often found in such biological data. def get_neigbours(M, k): nn = NearestNeighbors(n_neighbors=k+1, metric="euclidean").fit(M) References. Data mining for direct marketing: Problems and solutions. link] Ling, C.

Machine Learning 136

Machine Learning Metrics Data mining Knowledge Discovery 136

datapine

MAY 14, 2019

This interdisciplinary field of scientific methods, processes, and systems helps people extract knowledge or insights from data in a host of forms, either structured or unstructured, similar to data mining. If you want to become an Ipython legend, this is one of the best books on data science on offer at the moment.

Data Science 350

Data Science Machine Learning Data-driven Big Data 350

Sisense

AUGUST 11, 2019

BI lets you apply chosen metrics to potentially huge, unstructured datasets, and covers querying, data mining , online analytical processing ( OLAP ), and reporting as well as business performance monitoring, predictive and prescriptive analytics. But on the whole, BI is more concerned with the whats and the hows than the whys.

Business Intelligence 75

Business Intelligence Business Analytics Analytics OLAP 75

Sisense

MAY 11, 2021

Reporting Reporting contains the flattest and most cleaned version of our data. It often will collapse the metrics in a fact table to the level of a single dimension through a form of aggregation or lookback window. Importantly, both workflows for data analytics are supported by a set of data models that follow the same data pipeline.

Modeling 84

Modeling Big Data IoT Data Warehouse 84

Domino Data Lab

AUGUST 1, 2021

Because of its architecture, intrinsically explainable ANNs can be optimised not just on its prediction performance, but also on its explainability metric. Instead, you should focus on how techniques like PDPs and LIME can be used to gain insights into the model’s inner workings and how you can add those to your data science toolbox.

Modeling 139

Modeling Deep Learning Machine Learning Knowledge Discovery 139

The Unofficial Google Data Science Blog

JANUARY 14, 2016

The LSOS may do this by exposing a random group of users to the new design and compare them to a control group, and then analyze the effect on important user engagement metrics, such as bounce rate, time to first action, or number of experiences deemed positive. In addition to a suitable metric, we must also choose our experimental unit.

Experimentation 41

Experimentation Statistics Metrics Measurement 41

The Unofficial Google Data Science Blog

OCTOBER 7, 2015

Nevertheless, A/B testing has challenges and blind spots, such as: the difficulty of identifying suitable metrics that give "works well" a measurable meaning. In this blog post, we summarize that paper and refer you to it for details. This is essentially the same as finding a truly useful objective to optimize. 2] Ron Kohavi, Randal M.

Modeling 61

Modeling Experimentation Knowledge Discovery Testing 61

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

datapine

MARCH 31, 2022

S/He is responsible for providing cost-effective solutions to achieve business objectives, comparing operational progress against project development while assisting in planning budgets, forecasts, timelines, and developing reports on performance metrics. BI Project Manager. SAS BI: SAS can be considered the “mother” of all BI tools.

Business Intelligence 239

Business Intelligence Statistics Visualization Data-driven 239

Jet Global

MAY 9, 2024

Monitoring can include tracking performance metrics such as execution time and resource usage, and logging errors or failures for troubleshooting and remediation. It also includes data validation and quality checks to ensure the accuracy and integrity of the data being processed.

Data Lake 52

Data Lake Data Warehouse Business Intelligence Machine Learning 52

Jet Global

MAY 1, 2023

that gathers data from many sources. 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.” As a result, end users can better view shared metrics (backed by accurate data), which ultimately drives performance.

Analytics 52

Analytics Cost-Benefit Visualization Dashboards 52

The Unofficial Google Data Science Blog

FEBRUARY 29, 2016

Variance reduction through conditioning Suppose, as an LSOS experimenter, you find that your key metric varies a lot by country and time of day. At Google, we tend to refer to them as slices. And since the metric average is different in each hour of day, this is a source of variation in measuring the experimental effect.

Experimentation 40

Experimentation Metrics Statistics Measurement 40