Interesting article that helps explain the increasing issue with mass reliance on using Data Visualization tools to blend data and define business rules. These tools are great, but not a replacement for proper data management. Data Viz tools empower the end user, one user at a time. Data management should not be defined at the desktop, by individuals, and within mutliple tools. The possiblility for data inconsistencies are increased and there is no longer a clear-cut definition of what the data is that is being reported, it now becomes dependent on the definition created by an individual at that specific moment in time for that specific tool.
From large banks to popular online games, healthcare industry to major retail stores – everyone is enjoying the success of the NoSQL movement. Need a recent example? Obamacare (what your opinion on this may be) is launched on a NoSQL database system.
In my first post on the NoSQL databases we will take a short journey to the NoSQL world briefly covering the following points.
- What is NoSQL
- Why NoSQL is important now
- How NoSQL databases emerged
What is NoSQL?
- NoSQL-database.org defines NoSQL as “Next Generation Databases mostly addressing some of the points: being non-relational, distributed, open-source and horizontally scalable.”
- NoSQL does not represent a single database or technology. People use the term “NoSQL” to represent a family of databases and data stores…
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1. What is a Datawarehouse?
Ans. A datawarehouse is a subject-oriented, integrated, time-variant and non-volatile collection of data in support of management’s decision making process.
Subject-Oriented: A data warehouse can be used to analyze a particular subject area. For example, “sales” can be a particular subject.
Integrated: A data warehouse integrates data from multiple data sources. For example, source A and source B may have different ways of identifying a product, but in a data warehouse, there will be only a single way of identifying a product.
Time-Variant: Historical data is kept in a data warehouse. For example, one can retrieve data from 3 months, 6 months, 12 months, or even older data from a data warehouse. This contrasts with a transactions system, where often only the most recent data is kept. For example, a transaction system may hold the most recent address of a customer, where a…
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This year could be a good one for business intelligence (BI), with companies across the sector looking to grow as businesses in other industries do.
But with this in mind, what will be the biggest trends and differences in 2014?
The rise of the decision maker
According to many experts, this will be the year when the BI market finally moves away from being one that is primarily IT-centric and becomes a lot more user friendly.
Over the past few years, IT professionals have created, used and produced the reports that are associated with the software, but there are now more companies looking to get involved at the ownership level so they get a feel for what they are using.
This will mean that BI becomes more user-friendly and usable throughout the year, as opposed to being the very technical solution that is has often been criticised as being in…
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Over the past several years, the interest in “Big Data” has socialized the value of data to businesses. There are a host of companies developing platforms and tools to help companies utilize their data. While there may be “Big Data” skeptics out there, it’s impossible for IT executives to ignore the issue. This is all to the good, as it means that businesses are starting to take a serious look at the opportunity to use data to drive decision making, improve operational efficiencies and increase revenue. But companies that haven’t addressed these issues before find it difficult to know where to start. Having worked with and led data analysis teams for many years, I want to share some experiences about what works (and what doesn’t).
The Problem with Business Intelligence
The traditional approach in IT organizations to business intelligence is to define a problem, fund a project to create a…
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I can certainly see the issue with data blending highlighted by Budzinkski at the end of the article. My great concern with data blending within a visualization tool is just what he states. The data is not being managed in the proper places. If you attempt to expand your BI Toolbox, you have a problem with data consistency because data is not managed in a common place and needs to be constantly redefined. It is also too common of a practice to ’embed business rules at the desktop’. Data should be defined once and used the same way across the entire enterprise. I couldn’t agree more with the last 2 paragraphs. Excellent article.
In a recent TDWI article titled Analysis: MicroStrategy’s Would-Be Analytics King, Stephen Swoyer, who is a technology writer based in Nashville, TN, stated that business intelligence (BI) stalwart MicroStrategy Inc. pulled off arguably the biggest coup at Teradata Corp.’s recent Partners User Group (Partners) conference, announcing a rebranded, reorganized, and — to some extent — revamped product line-up.
One particular announcement drew great interest: MicroStrategy’s free version of its discovery tool — Visual Insight — which it packages as part of a new standalone BI offering: MicroStrategy Analytics Desktop.
With Analytics Desktop, MicroStrategy takes dead aim at insurgent BI offerings from QlikTech Inc., Tibco Spotfire, and — most particularly — Tableau Software Inc.
MicroStrategy rebranded its products into three distinct groups: the MicroStrategy Analytics Platform (consisting of MicroStrategy Analytics Enterprise version 9.4 — an updated version of its v9.3.1 BI suite); MicroStrategy Express (its cloud platform available in both…
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