Here are a few words about some of their concepts:
(1)db/database/Database -This is the OLTP database, the online things database, used to support production, such as the supermarket trading system. DB retains the latest state of data information, only one state! For example, every morning to get up and face in the mirror, see is the state, as for the previous day of the state, will not appear in front of your eyes, this is a db.
(2)dw/data warehouse/Data Warehouse --here is the state of the different time points in the DB, for example, every morning after washing the mirror, take a picture, every day, these photos into an album, then you can see the status of each day, This album is the Data Warehouse , he saved the data at different time points of the state , the same data information, the state of keeping different points of time, it is convenient for us to do statistical analysis.
(3) etl/extraction-transformation-loading--Used to complete the db-to-DW data dump, which "extracts" the state of a point-in-time in db, and "transforms" according to the storage model requirements of the DW The data format, and then "load" the process to the DW, it should be emphasized that the DB model is the ER model, followed byNormalization ofdesign principles, and DW's data model isSnowflake Typestructure or star structure, with the topic-oriented, problem-oriented design ideas, so the DB and DW model structure is different, need to be converted.
(4)olap--Online Analysis System, simply said is the report system, sales reports, statistical reports, and so on, this everyone is familiar with, of course, the statistics of OLAP should be more complex and richer, such as cutting, drilling and so on.
(5)dm/data mining/Data Mining--This digging, not a simple statistic, he isbased on probability theory or other statistical principles, the large data volume in DW is analyzed to find out the laws that we can't visualize., for example, if we take a photo every morning, the amount of body, but also record the head of the day to eat things, cucumber, pig legs, roast duck, and mood, if recorded 10 years, formed a 3,650 days of appearance and eating mood data, each of us recorded, 200,000 people recorded, then, We may, through these records, be able to analyze the objective laws of body appearance and diet; Another typical example is the British supermarket, after accumulating a large amount of data, after the data analysis mining, got a rule: put the baby's diapers and beer together, sales will be better-business experts after the conclusion , careful analysis, know the reason, because the British men like to watch more football, the wife of the child introduced a man in custody, the child urine needs diapers, and men to watch football like drinking, so two commodities have a close relationship, put together to sell better!
(6)bi/business intelligence/Business Intelligence -leadership, decision-maker, after obtaining the statistics of OLAP, and the scientific law obtained by DM, make appropriate adjustment to production, for example, ordered supermarket staff to put beer drink diapers together to sell, This is counterproductive to the DB modifying the inventory data-this is what the whole bi does!
Information technology after nearly 20 years of vigorous development, many industries have accumulated a lot of valuable data, the real Big data era has come, but also gradually reflects the importance of db-etl-dw-olap-dm-bi this line, I hope you can understand the value of this big data era, to seize the opportunity, there is a better future!
DB, ETL, DW, OLAP, DM, BI relationship structure diagram