Ensemble modeling is the process of running two or more related but different analytical models and then synthesizing the results into a single score or spread in order to improve the accuracy of predictive analytics and data mining applications.
In predictive modeling and other types of data analytics, a single model based on one data sample can have biases, high variability or outright inaccuracies that affect the reliability of its analytical findings. Using specific modeling techniques can present similar drawbacks. By combining different models or analyzing multiple samples, data scientists and other data analysts can reduce the effects of those limitations and provide better information to business decision makers.
One common example of ensemble modeling is a random forest model. This approach to data mining leverages multiple decision trees, a type of analytical model that’s designed to predict outcomes based on different variables and rules. A random forest model blends decision trees that may analyze different sample data, evaluate different factors or weight common variables differently. The results of the various decision trees are then either converted into a simple average or aggregated through further weighting.
Ensemble modeling has grown in popularity as more organizations have deployed the computing resources and advanced analytics software needed to run such models. In addition, the emergence of Hadoop and other big data technologies has led businesses to store and analyze greater volumes of data, creating increased potential for running analytical models on different data samples.
Disaster Recovery as a Service
Disaster Recovery as a Service (DRaaS) is the replication and hosting of physical or virtual servers by a third-party to provide failover in the event of a man-made or natural catastrophe.
Typically, DRaaS requirements and expectations are documented in a servel-level agreement (SLA) and the third-party vendor provides disaster recovery failover to a cloud environment, either through a contract or pay-per-use basis. In the event of an actual disaster, an offsite vendor will be less likely than the enterprise itself to suffer the direct and immediate effects of that disaster, allowing the provider to implement the DRP even in the event of the worst-case scenario: a total or near-total shutdown of the affected enterprise.
DRaaS can be especially useful for small to mid-size businesses that lack the necessary expertise to provision, configure and test an effective disaster recovery plan. Using DRaaS also means the organization doesn’t have to invest in — and maintain — their own off-site DR environment. An additional benefit is that RaaS contracts can be flexible as the business’ needs change. The downside, of course, is that the business must trust that the DRaaS service provider can implement the plan, in the event of a disaster, and meet the defined recovery time and recovery point objectives.
A data warehouse is a federated repository for all the data that an enterprise’s various business systems collect. The repository may be physical or logical.
Data warehousing emphasizes the capture of data from diverse sources for useful analysis and access, but does not generally start from the point-of-view of the end user or knowledge worker who may need access to specialized, sometimes local databases. The latter idea is known as the data mart.
There are two approaches to data warehousing, top down and bottom up. The top down approach spins off data marts after the complete data warehouse has been created. The bottom up approach builds the data marts first and then combines them into a single, all-encompassing data warehouse.
Typically, a data warehouse is housed on an enterprise mainframe server or increasingly, in the cloud. Data from various online transaction processing (OLTP) applications and other sources is selectively extracted for use by analytical applications and user queries.
The term data warehouse was coined by William H. Inmon, who is known as the Father of Data Warehousing. Inmon described a data warehouse as being a subject-oriented, integrated, time-variant and non-volatile collection of data that supports management’s decision-making process.
Does the early bird catch the worm? or is it Fish? It all depends if you live by the sea (so it is a Fish caught by the seagull) or in the inland (so it is a worm caught by some bird). For the bird, the catch is its food, it’s own opportunity. So… opportunities always exist! But it seems that you have to try to move near them, close to them, beside them. And if a fish is a better nutritional opportunity than the worm, the bird must fly near it, to gain with the respective pain.
Always be alert, always be ready, not anxious, yet ready. Always read, read something, always look for the scent of the new, for the scent of progress, of innovation. After all, when reading a book, when studying a course, we are all fishing for knowledge, for sentiment, for feelings, for experiences.
A good book, is a good fish, a big fish. Bon Appetite!
(if it interests you – read a good book on BI or Data Science)
GrUoBIApps – Admin
Apple announced this morning that its payments service Apple Pay will now support the ability to make donations to non-profits, starting today in the U.S. This includes both Apple Pay on the web, where it can be integrated into websites’ checkout flow, as well as within mobile applications. The changes are rolling out just ahead…
Samsung is giving customers a new incentive to use Samsung Pay, its mobile payments product. The company released Samsung Rewards today, which is a program that provides points whenever a user uses their Samsung Pay for a transaction. The points gathered through the program can then be exchanged for rewards including gift cards, Samsung products, and…
Οι εξελίξεις προχωρούν στον τομέα των ηλεκτρονικών πληρωμών με ραγδαίο ρυθμό & οι εμπλεκόμενες & ενδιαφερόμενες εταιρείες προωθούν τα προϊόντα τους & εφαρμόζουν όσο πιο γρήγορα μπορούν την στρατηγική τους. Πολλά βήματα έχουν να γίνουν ακόμη στον τομέα της ασφάλειας – ένα ζήτημα που αγγίζει δισεκατομμύρια χρήστες – & φυσικά θα έχει πάντοτε “χώρο” για βελτιώσεις αφού πάντοτε θα ισχύει το ρητό “ότι φτιάχνεται από άνθρωπο, χακάρεται & από άνθρωπο…”
Electric cars and hybrid vehicles can be incredibly quiet – so quiet that a populace used to cars that make noise can be hurt when sharing space with them. New NHTSA standards for automakers aim to help fix that with audible alerts hat are required on all new hybrid and electric going forward beginning September 1,…
Στην χώρα μας, εξελίξεις περί νόμων & εγκυκλίων & απαιτήσεων ασφαλείας για ηλεκτρικά αυτοκίνητα δεν πρόκειται να δούμε τα επόμενα 30 χρόνια, έχω την εντύπωση. Δεν είμαι φύσει απαισιόδοξος ή δύσκολος αλλά οφείλω να το πω και ας πέσει κάτω.