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All Blog Posts Tagged 'Warehouse' (15)

If Data is as Valuable as Gold, It’s Time to Polish Your Data Architecture

It speaks volumes of the world we live in today when headlines such as “The world’s most valuable resource is no longer oil, but data” and “Why Data May Be More Valuable Than Dollars” are commonplace. With the explosion of IoT and with that 2.5 quintillion bytes of data being created per day, the underlying power of this data comes as no surprise.

Unlike gold however, data is ubiquitous and being created at an exponential rate. So where’s the value in something that is everywhere?…

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Added by Amy Flippant on June 5, 2017 at 12:30am — No Comments

Modelling a Data Warehouse

When designing a model for a data warehouse we should follow standard pattern, such as gathering requirements, building credentials and collecting a considerable quantity of information about the data or metadata. This helps to figure out the formation and scope of the data warehouse. This model of data warehouse is known as conceptual model. General elements for the model are fact and dimension tables. These tables will be related to each other which will help to identity relationships…

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Added by Avesh Dhakal on June 8, 2014 at 7:54am — 1 Comment

Dimensional Modelling

There isn’t any specific standard to model data warehouse. It can be built either using the “dimensional” model or the “normalised” model methodologies. Normalised model normalises the data into third normal form (3NF) whereas dimensional model collects the transactional data in the form of facts and dimensions. Normalised model is easy to use as we can add related topics without affecting the existing data. But one must have good knowledge of how data is associated before performing…

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Added by Avesh Dhakal on May 29, 2014 at 4:12am — No Comments

Gather technical & business world

The Telecom market is saturating and to increase their turnovers, operators are very creative and launch many innovative offers combining devices (mobile phone, MP3 players...), software (music downloads,...) and network (IP calls, ...). On another level, operators would first like to set trustworthy relationships with their good clients and therefore identify them and propose them quality services. To do so, the advanced knowledge of the customers’ past experience is fundamental. In fact,…

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Added by Michel Bruley on February 5, 2014 at 12:13am — No Comments

Master Data Management Solutions

What is MDM and what does it involve?

MDM aims at referencing, managing and synchronising all the data across a company (e.g. products and customers data) to ensure the liability and preciseness. By using a good data management, the company will be able to simplify its processes, to avoid overlap and to ensure the quality and usability of the data. MDM has impacts on different levels for a company.  On the business side, it affects speed,…

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Added by Michel Bruley on January 2, 2014 at 12:48am — No Comments

“GHOST DEVELOPERS” AND BI CENTRE OF EXPERTISE: THE BELGACOM GROUP’S EXPERIENCE

 

Belgacom Group is the world 8th Telecom operator, it is 1st in Belgium for Mobile phone and landline services (e.g. 4,6 million mobile phone customers). The group employs 17 000 people, is owned (53, 5%) by the Belgium state and develop landline services under the brand names of Belgacom, Telindus, Skynet. Belgacom also develop a very specific approach for its strategic positioning by balancing the product leadership, prices competitiveness and the knowledge of its…

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Added by Michel Bruley on December 2, 2013 at 12:12am — No Comments

ERP Tools, Enterprise Data Warehouse and Warranty Management

For many years, manufacturers have been trying to outperform the competition by offering up to five warranties on a car, for example, overusing the warranty argument in their marketing. Moreover, warranty costs have gone through the roof and repeated callbacks have ended up tarnishing the image of many companies. Therefore, it is obvious that their favorite integrated management software is not going to solve the problem, as it requires the integration of data from the entire company and all…

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Added by Michel Bruley on September 3, 2013 at 10:00pm — No Comments

Big Data: Understand the customer course on the net before he buys

 

Marketing is being redefined by the changing habits of consumers, by the limitless choice for placing ads and the access to customers through a variety of channels. As a result, many companies are changing their plan of action and the allocation of their budgets for the different channels, including the web, campaigns, including mobile, social media, etc.



Recent studies which have analyzed the course of online shoppers, indicate that traditional marketing campaigns…

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Added by Michel Bruley on August 1, 2013 at 11:44pm — No Comments

Full Tilt Poker: Big Data Fraud Detection and Prevention

Full Tilt Poker is the second largest online poker room; it belongs to Rational FT which is a computer services company that develops software, business computer maintenance and performs operations based digital marketing. http://www.rfts.com/  



Two fundamental points of running a poker room online are the integrity of the site and the trust of customers. Players must be completely sure that they are protected against fraud. Negative publicity…

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Added by Michel Bruley on May 6, 2013 at 1:39am — No Comments

Big Data means to support Buzz Marketing actions

 

What is buzz marketing? In the strict sense of the term, buzz marketing is creating noise around a product, service, company or brand. For example you can recruit consumers, preferably proactive volunteers who influence their peers, and help them to try your products in good condition before pushing them to talk about their experience.



The buzz is one of the most powerful forces in the market, and knowing how to master this important marketing channel is critical. Word of…

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Added by Michel Bruley on March 7, 2013 at 4:21am — No Comments

Big Data: Hadoop is not the universal panacea



IT market studies expert indicate that the advanced analysis of various data and the management of an increasing volume of data, are among the five priorities large enterprises CIOs and companies at the forefront of the world of internet. Big Data is thus increasingly important, and a growing number of companies complete their decision-making infrastructure, with new analytical platforms to improve their efficiency and profitability.



First experiences Big Data observations show…

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Added by Michel Bruley on February 4, 2013 at 10:53pm — No Comments

What Big Data means at LinkedIn?

LinkedIn was founded in 2003, is currently revenue 243 million and employs 1797 people. This is not what we call a large company. However, LinkedIn has 175 million members in 200 countries including 50% outside the U.S., two new members join the network every second, and analysts said that all "executive" of the Global 500 are members. Under these conditions, LinkedIn is facing a high volume of data to process. Indeed their information system must support 2 billion a year of research carried…

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Added by Michel Bruley on December 3, 2012 at 3:16am — No Comments

Big Data: Opinions & Sentiments Analysis

Analyzes of texts put lights in two main types of information “facts and opinions”. Most current treatment methods of textual information aim to extract and use factual information, this is the case for example of research we do on the web. Analysis of opinions is concerned about feelings and emotions expressed in the texts, it has grown much today because of the space taken from the web in our society, and the very large volume of daily comments expressed by consumers with the advent of the…

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Added by Michel Bruley on October 2, 2012 at 10:43pm — 5 Comments

Hadoop Technology Stack

The Hadoop stack includes more than a dozen components, or subprojects, that are complex to deploy and manage. Installation, configuration and production deployment at scale is challenging.

The main components…

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Added by Michael Walker on August 22, 2012 at 9:40am — No Comments

Which IT infrastructure for Big Data?

A Big Data decision support system requires particular capabilities in terms of volume, variety of data and processing speed.



Today companies to improve their knowledge models and forecasts, do not hesitate to take into account hundreds of factors, and do not hesitate to bring up new means of analysis that can handle large volumes of data. But the processing of large volumes of data is a challenge for traditional BI infrastructure. Storing large volumes is not a problem, but…

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Added by Michel Bruley on July 31, 2012 at 11:03pm — No Comments

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