1 00:00:04,970 --> 00:00:10,990 Data analysis and data science that was the first step in this process will be collect data. 2 00:00:11,300 --> 00:00:18,170 We collect data from sources, mobile phones, computers, recording devices, communication events 3 00:00:18,560 --> 00:00:26,360 and interaction between Verizon and Verizon, device device and device and moves so that the fight occurs 4 00:00:26,360 --> 00:00:34,850 in many forms as exiles see as we just want to see that appeases and the more second step is to connect 5 00:00:34,850 --> 00:00:42,950 and the process that used by some to make it very easy to read that from these sources and forms of 6 00:00:42,950 --> 00:00:52,100 data files with the help of Pacific useful by some of the else and library we mentioned before by Banda's 7 00:00:52,310 --> 00:01:01,930 Seabourne Metalocalypse Random Clean Road that after we process and organize the files and for me that 8 00:01:01,940 --> 00:01:05,270 that means still contain duplicates or errors. 9 00:01:05,600 --> 00:01:14,000 So we will clean that to reduce these errors, to increase the quality of data and the results from 10 00:01:14,000 --> 00:01:19,880 the data analysis process, throw out the following step on a copy of that. 11 00:01:20,150 --> 00:01:28,520 Corrected that AFIS for mid-state, remove duplicates, rows, columns, correct timestamp and format 12 00:01:28,520 --> 00:01:36,890 of that dream incorrect golems name to facilitate the analysis process match golems, which contains 13 00:01:36,890 --> 00:01:45,680 the same data or complete each other's correct data types and every column of the data files to be the 14 00:01:45,680 --> 00:01:54,140 same that time if necessary and helpful manager data files and to complete the missing data in every 15 00:01:54,140 --> 00:01:56,150 column of the data files. 16 00:01:56,210 --> 00:02:01,240 If you can otherwise delete neglected, unhelpful missing data columns. 17 00:02:01,250 --> 00:02:06,350 Correct the spelling of any string data types in the data file. 18 00:02:06,440 --> 00:02:15,170 Make another copy of the claim that for the analysis process, explore and analyze that we analyze data 19 00:02:15,170 --> 00:02:21,050 by using technical exploratory data analysis, which should help us to detect if there are additional 20 00:02:21,050 --> 00:02:23,150 problems in that any way. 21 00:02:23,570 --> 00:02:31,250 So this will be repeated throughout the whole data analysis conclusion and the communication of data 22 00:02:31,250 --> 00:02:32,870 analysis isn't lost. 23 00:02:32,870 --> 00:02:39,200 A step of data analysis process has to reach a conclusion and communicate your conclusion to decision 24 00:02:39,200 --> 00:02:39,950 makers. 25 00:02:39,980 --> 00:02:46,700 Once you reach your conclusion about problems with your data analysis can solve, you will make are 26 00:02:46,700 --> 00:02:54,050 able to help decision makers to take action about specific business issues that your organization facing. 27 00:02:54,050 --> 00:03:00,740 Making a good report showing the business problems solution is one of the most important data and is 28 00:03:00,740 --> 00:03:01,500 the task. 29 00:03:02,750 --> 00:03:03,930 Thanks for watching. 30 00:03:04,100 --> 00:03:05,680 See you next week. 31 00:03:05,700 --> 00:03:05,900 You.