Sisense

JULY 14, 2019

You also want to choose ISO-compliant analytics software and cloud database partners. Whatever platform you choose should also allow admins to easily manage security settings and user access from one place and give them usage analytics to determine who’s doing what with the system and make sure that no one is misusing their access.

Software 75

Software Strategy Data Warehouse Modeling 75

Peter James Thomas

JUNE 20, 2019

A decade later, Gartner had some rather sobering thoughts to offer on the same subject: Gartner predicted that through 2008, about 60% of organizations that outsource customer-facing functions will see client defections and hidden costs that outweigh any potential cost savings. And reduced costs aren’t guaranteed […].

Cost-Benefit 55

Cost-Benefit Data Warehouse Consulting Data Science 55

AWS Big Data

JUNE 29, 2023

Amazon Kinesis Data Analytics makes it easy to transform and analyze streaming data in real time. In this post, we discuss why AWS recommends moving from Kinesis Data Analytics for SQL Applications to Amazon Kinesis Data Analytics for Apache Flink to take advantage of Apache Flink’s advanced streaming capabilities.

Data Analytics 74

Data Analytics Analytics IoT Data Lake 74

AWS Big Data

APRIL 20, 2023

In a modern data architecture, unified analytics enable you to access the data you need, whether it’s stored in a data lake or a data warehouse. If we run a similar query from the Amazon Redshift Query Editor, we can see that there are actually five such venues within that time frame.

Visualization 78

Visualization Data Warehouse Big Data Data Lake 78

BizAcuity

MAY 10, 2022

2008: Microsoft announces Windows Azure (PaaS) with Azure Blob storage (S3 competitor). 2012: Amazon Redshift, the first of its kind cloud-based data warehouse service comes into existence. Fact: IBM built the world’s first data warehouse in the 1980’s. The platform wasn’t received well at the beginning.

Data-driven 52

Data-driven IoT Unstructured Data Data Lake 52

Domino Data Lab

JULY 22, 2019

You know, case in point, if you were to talk about predictive analytics 20 years ago, the main people in the field would have laughed you out of the room. Predictive analytics, yeah, not so much.” The data governance, however, is still pretty much over on the data warehouse. Then we roll out a decade later.

Data Science 109

Data Science Machine Learning Data Governance Modeling 109

Occam's Razor

MAY 18, 2010

I have said: All data in aggregate is "crap" Because it is. One of my earliest blog posts extolled the glorious virtues of segmentation: Excellent Analytics Tip#2: Segment Absolutely Everything. Many paid web analytics clickstream analytics tools, even today (!), Of course Yahoo! The Problem. All visits.

Analytics 123

Analytics Key Performance Indicator Metrics Measurement 123

Jen Stirrup

OCTOBER 30, 2022

As a first step to customer insight, analytical tools can summarise and aggregate historical information about customers. One particular technology which is good for summarising and aggregating data is called OLAP (On Line Analytical Processing). This model can assist in decision making and in focusing marketing efforts.

Data mining 52

Data mining Predictive Analytics Cost-Benefit OLAP 52

Cloudera

JANUARY 3, 2019

Our pre-merger customer bases have very little overlap, giving us a considerable enterprise installed base whose demand for IoT, analytics, data warehousing, and machine learning continues to grow. It’s clear today that the data warehouse industry is undergoing a major transformation. Our bet in 2008 has proven prescient.

IoT 75

IoT Machine Learning Data Warehouse Enterprise 75

Cloudera

OCTOBER 3, 2018

In 2008, I co-founded Cloudera with folks from Google, Facebook, and Yahoo to deliver a big data platform built on Hadoop to the enterprise market. We believed then, and we still believe today, that the rest of the world would need to capture, store, manage and analyze data at massive scale.

Uncertainty 75

Uncertainty IoT Risk Reporting 75

Jet Global

APRIL 5, 2021

For example, pension funds must be able to pay pensioners during any economic conditions, including a crisis like 2008. Asset and liability financial models are primarily used by financial institutions (banks and insurance companies) and pension funds (corporate or public) to manage their financial objectives.

Modeling 98

Modeling Forecasting Metrics Finance 98