Jen Stirrup
SEPTEMBER 30, 2021
Azure ML can become a part of the data ecosystem in an organization, but this requires a mindshift from working with Business Intelligence to more advanced analytics. How can we can adopt a mindshift from Business Intelligence to advanced analytics using Azure ML? AI vs ML vs Data Science vs Business Intelligence.
datapine
SEPTEMBER 29, 2022
Therefore, there are several roles that need to be filled, including: DQM Program Manager: The program manager role should be filled by a high-level leader who accepts the responsibility of general oversight for business intelligence initiatives. The program manager should lead the vision for quality data and ROI.
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Jen Stirrup
NOVEMBER 30, 2021
In this session, we will start R right from the beginning, from installing R through to data transformation and integration, through to visualizing data by using R in PowerBI. Then, we will move towards powerful but simple to use datatypes in R such as data frames.
FineReport
APRIL 21, 2024
From addressing implementation challenges to conducting a comparative analysis of leading options, we delve into how embedded BI tools empower organizations to make informed decisions and drive business intelligence initiatives with unprecedented efficiency and precision. What Are Embedded BI Tools?
Cloudera
AUGUST 17, 2021
When we announced the GA of Cloudera Data Engineering back in September of last year, a key vision we had was to simplify the automation of data transformation pipelines at scale. Let’s take a common use-case for Business Intelligence reporting. Figure 2: Example BI reporting data pipeline.
AWS Big Data
OCTOBER 11, 2023
Traditionally, such a legacy call center analytics platform would be built on a relational database that stores data from streaming sources. Data transformations through stored procedures and use of materialized views to curate datasets and generate insights is a known pattern with relational databases.
IBM Big Data Hub
JANUARY 18, 2023
Data platform architecture has an interesting history. Towards the turn of millennium, enterprises started to realize that the reporting and business intelligence workload required a new solution rather than the transactional applications. A read-optimized platform that can integrate data from multiple applications emerged.
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