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Every woman has an issue with managing her belongings. From clothes to accessories, she needs that one thing that will help her store all her stuff in one place. I cannot imagine being unorganized and I’m sure most of you reading this would agree with me. Why is it so hard to be organized? Most of the time, I was ragged for that very reason of being an Obsessive Compulsive person.
Now the reason I brought this up was because I happened to read several articles on data warehousing and I was reminded of myself. Just like my basic obsession of having all my belongings in one place in the right order, companies today expect the same. There are chances of your ideas of data warehousing being hazy. There are a lot of people who are still clueless about the same.
Data warehouses are used widely within organizations today. It is believed that, in the next few years the use of it will gradually increase. In challenging times, making smart decisions and efficiently managing data becomes very crucial, that’s when data warehouse fits in just perfectly. The concept of data warehousing is not hard to understand. The notion is to create a permanent storage space for the data needed to support reporting, analysis, and other BI functions.
The concept of data warehousing is simple. Data is extracted periodically from the applications that support business processes and copied onto special computers. There it can be validated, reformatted, reorganized, summarized, restructured, and supplemented with data from other sources (The Data warehouse is my accessory box. Just like managing my array of scattered accessories into mini boxes, in turn stored in one large box). The data warehouse becomes the main source of information for report generation, analysis, and presentation through ad hoc reports, portals, and dashboards. (It becomes easier for me to locate which accessory is kept in what box)
1. Runs on computers dedicated to this function. (My mind)
2. Runs on a database management system (DBMS) (series of other mini boxes that stores my accessories)
3. Retains data for a long period of time. (Stores my accessories for a long period of time)
4. Combines data obtained from many sources (Stores an array of accessories that were scattered in different places)
5. Built around a carefully designed data model that transforms production data from a high speed data entry design to one that supports high speed retrieval. ( My choice of picking the perfectly designed box to accommodate all my accessories and differentiating between a good box and a mediocre one)
The most difficult thing about creating a good data warehouse is the design of that model around which it was built. Decisions need to be made as to the names to give to each field, whether each data model needs to be reformatted and what meta data fields should be calculated and added. Once a data warehouse is operational, it is important that the data model remains stable. If it does not, then reports created from the data will need to be changed whenever the data model changes.
Once a data warehouse is in place and is well populated with data, good stuff start cracking. Some of them are as follows:
1. Generation of scheduled reports
2. Packaged analytical applications
3. Ad hoc reporting and analysis
4. Dynamic presentation through dashboards
5. Drill down capability
6. Data mining
These benefits is what makes BI based on data warehousing a crucial management tool for companies that have reached a certain level of complexity.
Apple is operating a multiple-petabyte Teradata system. Apple uses the data warehouse to get a better understanding of its customers across product groups. Now every piece of identifiable information and those i Tunes interactions generate a lot of data that goes into the system so the company knows who’s who and what they’re up to.
The retail giant deployed Teradata’s first-ever terabyte-scale database in 1992, and it has grown a bit since then. Its operational system was at 2.5 petabytes as of 2008, and is certainly leaps and bounds bigger by now — likely well into the double digits when you consider it operates separate ones for Walmart and Sam’s Club as well as a backup system. The analytics efforts have essentially helped Walmart become a massive consignment shop.
eBay has two systems in place, and they’re both big. Its primary data warehouse is 9.2 petabyes; its “singularity system” that stores web clicks and other “big” data is more than 40 petabytes. It has a single table that’s 1 trillion rows. Yes, this is smaller than the 50 petabytes worth of Hadoop capacity eBay added last year, but Teradata is quick to point out that all of its systems support data into and out of Hadoop, so it’s not as if eBay is operating two entirely distinct data environments.
Since 1971, Starbucks Coffee Company has been committed to ethically sourcing and roasting the highest-quality coffee in the world. They use a high performance enterprise data warehouse containing sales, marketing, store management, point of sale, customer loyalty, and supply chain data to drive more informed business decisions at the corporate, regional, and store levels.
Continental Airlines decided it wanted to keep its customers’ happy and began assessing them by lifetime value and began making alternative arrangements for them as soon as the airline realized flights would be delayed.
A luxury car company used Aster Data to analyze the pattern of failures for various components inside its cars. It found out that lighting, seats and infotainment often failed together (they’re on the same circuit) and began inspecting all three when a customer comes in for service on any of them.
The value of data warehouse increases over time and it pays to start putting everything down in one place. A delay in having it could cost you as your competitors have grabbed the opportunity.
1. Hard savings come from things like discovering lost discounts in payables or that sales people are offering discounts beyond approved limits.
2. Real time consolidation of financial data becomes practical and debates cease over which source of data is correct.
3. The IT costs and staff dedicated to reporting are greatly reduced.
4. By providing data from various sources, managers and executives will no longer need to make business decisions based on limited data or their gut.
5. A Data warehouse stores large amounts of historical data so you can analyze different time periods and trends in order to make future predictions.
6. Data warehouse works in favor of saving you so much time. They save time by storing a company’s information at one location. Rather than having it in different locations, a centralized one makes it better.
The data your company generates is of great value to your business. You want to make sure that all your data is secure and is accessible at any point of time. But today, data has been growing enormously and companies are finding a way to manage them. Data warehouse seems to be a good bet in this case. But the real question is, does your company really need one?
The use of spreadsheets has become of great value since it is one of the most important business tools today. A huge amount of data can be stored in these spreadsheets. The problem arises when the size of the data begins to increase. Each department has spreadsheets that you will need to pull data from in order to generate a report. If this is the case you find yourself creating manual reports, which can take a lot of your time. When this happens, data warehouse comes in to the picture to make things easier, since it is difficult to find the data as it is spread across different sheets.
If you’re developing a report, only to find out that you need to wait for colleagues to provide the information on their spreadsheets, or to analyze their data, you could find yourself waiting for a longer time. Implementing a data warehouse can help centralize data and make it available to all team members more effectively. This cuts down the time spent actually having to track it down and communicating with colleagues.
When team leaders or members in different departments create reports, the data or findings are different from yours, or other reports. Not only is this frustrating, it is also time consuming to sort out and could lead to costly mistakes. If at any time you feel that there is inconsistency in your data, then maybe you could think over getting a data warehouse.
Ideally, we should be able to generate a report using existing data almost instantly. When generating a report if you find that you have to keep going to different sources to check if the data is updated, or keep manually updating other sources, you will notice the amount of time needed to develop a report.
Because data warehouses consolidate data, you only have to turn to one source for data. Combine with the fact that many data warehouses can be set up to automatically update if source data is updated or changed, and you can guarantee that the data you are using is always correct.
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