Instructor: David Schuff, Section 003

Weekly Question #6: Complete by March 30, 2017

Leave your response as a comment on this post by the beginning of class on March 30, 2017. Remember, it only needs to be three or four sentences. For these weekly questions, I’m mainly interested in your opinions, not so much particular “facts” from the class!If you sign in using your AccessNet ID and password you won’t have to fill in the name, email and captcha fields when you leave your comment.

Here is the question:

Take a look at the SpotCrime website. Type in a few zip codes to see crime statistics in different areas. Would you consider this more an example of data analytics/data mining as we’ve discussed it this week, or more like the OLAP/Pivot Table analysis we have been doing over the last week or so? Explain your reasoning.

48 Responses to Weekly Question #6: Complete by March 30, 2017

  • After taking a look at the website, I would consider the crime statistics to be more analytics/data mining. I feel this way because the data shown is most likely collected, and then transformed by being pinpointed on the map. By seeing the data on a map, the viewer is able to analyze it and see areas where similar types of crimes occur as well as areas where crimes are more prevalent.

  • I would consider this as more of an example of OLAP analysis because Spot Crime stores and uses historical data from police agencies and validated sources. They then use the information to plot accurate and up-to-date crime map based on geographic location. Although they said they analyze crime trends in neighborhoods, the map itself only shows historical crime data, not the crime trend.

  • SpotCrime’s data is more of an example of OLAP/Pivot analysis. The data displayed shows what crimes are happening or has happened in the past. For data analytics/data mining, the data from SpotCrime does not tell you why a crime is occurring or there is not enough to data to to infer why the crime occurred.

  • SpotCrime is likely based on OLAP/Pivot Analysis due to the results it presents. After entering the address, the user sees a map and a crude table below showing the location, types, and other details of the most recent crimes in the neighborhood. However, this is simple an entry-by-entry representation of past incidents, grouped by categories and filtered by the input addresses. Because it involves no analysis of trends, causes, predictions or generalizations, it does not uncover implicit and useful information and thus is not an example of data analysis / data mining.

  • I’d have to say that it’s an example of OLAP analysis, as it refers to confirmed crimes of the past. There really isn’t any information as to how these crimes occurred, nor does it provide us with any reports regarding them.

  • I think this is an example of OLAP/Pivot Table analysis. It allows you to specify the time frame that you wish to look at, and the area that you are interested in viewing and then it returns some results. This is comparable to what we did in the last assignment where we had to find product sales of certain colors within a certain time frame.

  • I think SpotCrime is more an example of OLAP because it says what has happened in the past, but it can’t tell us why crime happens or predict it. One can use the data to possibly find the areas with the most crime and when it occurs, which is more like data mining.

  • I would consider spot crime as OLAP/Pivot Table. I say this because it only gives information about what has already occurred, and is not doing any further analysis/predictions on the data.

  • SpotCrime is more like the OLAP analysis rather than Data Mining. It does not provide any further analysis or patterns using the data it retrieves. Rather it just visualizes various data points by filtering by address and provides information for each crime. No algorithm or formula is used to analysis the data to provide real business value.

    • I totally agree. SpotCrime isn’t transforming the data in any way. It is likely basing this visualization off a pivot table, where crimes are sorted by zip code.

  • I would consider this SpotCrime Website as OLAP/ Pivot Table analysis. Because the website does not really store any analysis or prediction of the future crime. It essentially recorded all the crimes that occurred in the past; It also shows the details of the crime as we change the address which is equivalent to the filter function in Pivot Table.

  • Base on my understanding of the pivot table and the website, I see that they are alike. In pivot table, I use the historical records and the filter and values to make a table with the data I want. This website serve a similar function. It use historical crime data and filter them by Zip code to show information but not crime trend.

  • When I typed in my zip code, 19121, I was amazed to see how much crime there actually is in North Philly. Just in one day, there were over 30 different types of crimes with burglary’s and assault’s being the most frequent. I think this website is an excellent model of data analytics. Just hearing about the number of crimes in the North Philadelphia location is one thing, but seeing all the crimes pinned out on a map is another. I think the website models data analytics because it has the ability to log each crime with its respective location and ranks the crime based on severity and its legal formality. It even goes as deep to tell me at what time the crime occurred and the exact address of the incident. This website takes a mass amount of data and sorts it out for an enhanced level of analyzing. It gives you the ability to sort through the crimes to analyze further.

  • SpotCrime is an example of an OLAP because it gives us information about the past. I think in a way it could be argued that it is a data mining example because crime can often be repeated in an area, so past crime records could potentially tell you what to look out for in certain areas. But it does not tell you why certain crimes happen, so I believe it is an example of OLAP.

  • I believe this website is closer to a OLAP/Pivot table. My reason for this is that the information presented here has only occurred in the recent past what the information represents and does not provide any data on why or how the information came to be. Which is more in line with data mining.

  • After looking at SpotCrime, I would consider it to an example of OLAP/Pivot table because the chart shows crime status from the past. Data analysis/data mining would show more of a statistical and reasoning behind each of the crime status but it is not the case in SpotCrime. It just simply shows the different categories of crimes.

  • SpotCrime is more similar to pivot tables than data mining/analytics because it is taking past data and representing it in a easy to understand visual format. Data mining and analytics would be using a predictive model to find things like where a crime is likely to happen in the future, using the past data to predict the future.

  • SpotCrime’s information is a greater amount of a case of OLAP/Pivot investigation. The information showed demonstrates what wrongdoings are going on or has occurred before. For information examination/information mining, the information from SpotCrime does not disclose to you why a wrongdoing is happening or there is insufficient to information to induce why the wrongdoing happened.

  • I would say it is more like an OLAP/Pivot Table, because you can select a state or drill down to a specific zip code. It is also easily understandable visualized information. It does not provide any insights or predictions as a data mining or analytics tool would be expected to.

  • After looking at the data, I would say that SpotCrime is more OLAP/Pivot table because the chart shows crime data from the past. There is also no reasoning behind the data that is presented, which would be more data analysis/mining.

  • I think SpotCrime is an OLAP/Pivot table example, because of the nature of the data. For example, pivot tables are based on a set of historical data, and we used the pivot table to frame and answer questions we want to answer using the data. I visualize SpotCrime as almost the same process. For example, SpotCrime gathers historical data from a host of police blotter sources, and the user asks a question to be answered by the data using a zip code or address.

  • SpotCrime is definitely more similar to OLAP/Pivot Tables than to data mining/analytics. It is more similar to the OLAP/Pivot tables because the information that the website has is from the past. It is a record of past incidents that are presented in an easy to understand and visually satisfying format. It is not an example of data mining/analytics because it is not using the information that it has to make predictions about the future. It also does not show how or why the information happened.

  • SpotCrime is more similar to pivot tables than data mining because it does not tell the user why the crimes are happening, it just shows the information. SpotCrime also does not predict possible future crimes, which is a characteristic of data mining. SpotCrime has the potential to be used to predict crimes and determine why crimes are occurring where they are, but the site alone purely shows the information.

  • The SpotCrime website is more similar to Pivot Tables because it takes a large amount of criminal records of different categories and allows the user to enter an address or zip code, filter, to only analyze a certain section of the data. It then displays the recent crimes reported in the area and types of crime. In a Pivot Table, the rows could be the zip code and the values would be the total amount of crimes committed with that zip code.

  • The website Spotcrime is more similar to pivot tables rather than data mining and analytics. It is more similar to pivot tables and OLAP because it has crime status from the past as well as filters that allow you to show the data you want where as data mining/analytics would show more reasoning and possibly look for where crimes could happen.

  • To me the SpotCrime website is an example of an OLAP/pivot table as it shows records of crimes that happened. The website doesn’t give any suggestions or predictions; it only extracts data from police databases. Therefore, SpotCrime is OLAP and not data analytics/ data mining.

  • After visiting the SpotCrime website I was actually very impressed with how useful such a simple website could be. I would consider it to be more similar to OLAP because the crimes displayed on the website have obviously already occurred and its using an online tool to demonstrate the data collected. It would be more data analysis/data mining if they used the data they collected on the crimes to determine future acts of crime in that certain area.

  • I would consider SpotCrime very similar to OLAP/Pivot Table Analysis. When you input information, it’s essentially slicing a cube for measured facts; exactly like we do for Pivot Tables. The data itself could be applied and used for analytics (i.e. aggregate data across multiple zip codes and determine statistically what type of crimes are more probable for certain areas) but SpotCrime itself does not do that and it would be difficult given how they present the measured fact (it’s not in an interactive table, its more like a list).

  • It is an example of OLAP/Pivot Table Analysis. The map itself does not really tell us anything. We can see what crimes happened and where they occurred, but that is it. I feel like someone could do data analysis using the SpotCrime data and figure out trends. But the website itself is just OLAP/Pivot analysis. It just puts all of the information in one place.

  • Spotcrime could be considered as OLAP/Pivot Table type of information. It is taking recorded crimes from the recent past and then presenting them with a legend. Data mining would be more about predicting future crimes based on patterns and answering questions related to crime.

  • It is more of an example of pivot tables than data analytics. That is because restricting the map to a certain area is similar to choosing dimension and adding filters on a pivot table. Also, the fcat that there is no analysis presented with the data further proves that this is not an example of data analysis.

  • Spotcrime is more of an OLAP/Pivot Table information type because of its range of analytical data. Similar to pivot tables, Spotcrime allows the user to get information from the past, whereas, data analytics gives you up to date real time information. Data analysis also includes more charts, numbers, and statistics when you use Google Analytics and Spotcrime does not.

  • I personally think that this website is using OLAP/ pivot table, because it is using information from another source, like the time of crime/ location/ crime type/ etc, and displaying that info in an easy to view format. It’s also gathering only the historical data. I would say that it uses data mining, but it isn’t generating new info its just displaying it differently.

  • I think that SpotCrime is an example of OLAP/Pivot table because the website does not provide analysis and predictions for the crime. It provides the data about the crime that occurred. People are able to view where and what crime occurred.

  • SpotCrime seems to be a perfect example of OLAP/ Pivot Table Analysis. The website has clearly already gathered the data and categorized it efficiently so that filters like zip code or city can be utilized to display crime rates in particular areas. The filters are an example of slicing a data cube to display the information desired.

  • After taking a look at the website and searching my home address, it was eye opening to see what occurs in your surrounding areas. I believe you can conclude the data presented on Spotcrime would be OLAP/Pivot Table, because the information presented is from the past and it gives you basic facts. There is no explanation for the data, if reasoning was applied you would be able to further determine patterns and provide a more in depth analysis of the data.

  • After reviewing SpotCrime I see it more as an OLAP/Pivot Table source. It reminded me of dragging and dropping things into values and rows. Such as the row or zip code 19121 and the values or the crimes that occurred in this zip code.

  • Spotcrime is an example of OLAP/ Pivot Table analysis. It does not give analysis about future crime prediction, but it has the ability to sort and filter crimes based on area and type of crime that have already happened.

  • I think that SpotCrime is an example of OLAP and pivot tables because it closely resembles the functionalities of these tools. The search feature is essentially defining your “data set” and the results on the map is your summary information. All information displayed is based on past occurrences. The site gives you options to filter by crime type. There is an analytics section on the website that displays the crime data for the month in a series of charts but there isn’t any predictive functions that you might see with data mining.

  • It seems more like OLAP than analytics. It presents a visualization of the crime data, but the data isn’t being used for analytics. If it used the crime data to make inferences of other trends that are related than it would be more like data analytics.

  • I agree with the rest of the class that SpotCrime is much more similar to OLAP/Pivot Tables than to data mining/analytics. This is because the information that the website has is more related to historical data from past transactions. The series of past records are presented in a simple format and visually easier to interpret than a lot of data models. Since the information being displayed does not convey future predictions, or explain how/why the incident occurred, it would not be a clear efficient example of data mining/analytics .

  • I would consider SpotCrime to be an example of OLAP/Pivot Table analysis because it is summarizing past events through the use of dimensions. The fact in this case is the crime and the dimensions are the time and location. To be considered an example of data analysis/data mining SpotCrime would have to also include crime predictions based on past crimes at similar locations and at similar times.

  • In my opinion, this website seems more based on OLAP/Pivot Table analysis because it represents real things that happened, where they happened, and grouped by the crime type. Therefore, it seems that the mechanics of the website really just use something like a pivot table to reformat police reports and incidents that already occurred, and make them more friendly for concerned citizens to utilize. Additionally, the entire premise of the website is based on measured facts that people can “slice” or filter to take a closer look at what is going on near their homes. Based on these ideas I certainly feel like the website is more based on OLAP/Pivot Table analysis.

  • I would consider this as OLAP/Pivot table analysis. Data analytics/data mining would make predictions for future crimes where as SpotCrime simply tells us what kind of crimes occurred in the past and has no reference to possible future crimes.

  • I consider this to be an example of OLAP/Pivot table information. The information is being presented in certain areas where the data exists. Data analysis would be using that information to predict trends or future crimes based on patterns in the data.

  • After my visit to the Spotcrime website, I have came to the conclusion that the site would be considered an OLAP/Pivot Table. Reason being that the site gives you information about crimes that have already happened. For it to be considered Data mining, the site would’ve have to provide a prediction of crime that will occur based on patterns of past crimes.

  • After looking at the website, I believe that it is more of an example of OLAP/Pivot Table Analysis. The zip code that you enter serves as a filter that only shows crimes within that specific area. Additionally, it can be sorted by crime since each has a different icon.

  • The Spot Crime site is an example of an OLAP/Pivot Table Analysis. The results for a particular zip code or city are based upon past historical data collected from police departments and represented in specific categories and locations based upon what crime was committed and at what location. The site does not offer any specific analysis on why these events occur or how the results have changed over time which leads me to think that this is not an example of an analytical/mining analysis.

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