What is data warehousing? In the world of business intelligence, a data warehouse (DW or DWH) is the term used to describe a storage centre, or database, which is used strictly in regards to reporting and analytical purposes. A data warehouse is a compilation of data deposited from various sources, from operational systems such as marketing or sales, into a central location. The function of the warehouse is primarily to store data used for supporting managerial level business decisions. This warehouse would be regularly maintained and managed by a data warehouse developer.
Data warehousing warrants a developer to keep everything flowing properly. What is a data warehouse developer? This is a person, or team, who is responsible for the development of the operational systems from which data is ultimately extracted for future reference. This extraction load is called an ETL (extract transform load).
An ETL-based data warehousing process consists…
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Dave Henschen, the executive editor of InformationWeek, released InformationWeek’s 2014 Analytics, BI, and Information Management Surveyin Q4, 2013 to preview how organizations expect to capture, analyze, report, and act on their data. The utilization of business intelligence plays a significant role in all four of these aspects. The main takeaway from the study shows the trend towards less complex and more visual analytics.
2013 was a big year for analytics and Business Intelligence (BI) products as 35 percent of survey respondents have standardized at least one analytic or BI product throughout their company. This is up from just 30 percent of organizations going into 2013. Clearly organizations are finding value in Business Intelligence tools as 97% of responding organizations deploy analytics and BI in some capacity.
The biggest concern with analytics and BI is the data quality, as 59 percent of participants considered this the biggest barrier to successful…
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Wow, I found the statement below, from Magic Quadrant for Business Intelligence and Analytics Platforms, very interesting. I have found that having the best of both worlds; ease of use/availability for business users and the ability to maintain enterprise wide governance has been an issue. It will be interesting to see what products emerge that can provide for both.
The most notable change in this year’s Magic Quadrant is that all the vendors in the
Leaders quadrant have been moved to the left in terms of Completeness of Vision. This
reflects the fact that no one vendor is fully addressing the critical space in the
market for “governed data discovery” — in other words, platforms that address both
business users’ requirements for ease of use and enterprises’ IT-driven requirements.
This is great because it addresses the important reasons for having data governance. Because Tableau can essentially be used by the masses, it makes it much more likely that data can be grabbed and interepretted and defined by the user, not the enterprise. Even though a tool makes it easier for end-users to use the data, doesn’t mean the data should no longer be properly governed. It is important to remember Tableau is a tool used to visualize and analyze the data as it has been defined, not to recreate data depending on each user’s interpretation.