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Transcript

Welcome, everyone, and thank you for joining us today for the managing data sets and ÃÛ¶¹ÊÓƵ Commerce Intelligence Webinar. I’m Webster Love and I’ll be your host for today. Joining me is your presenter for today’s session, Deepak Chahar. More from the product team for ÃÛ¶¹ÊÓƵ Commerce Intelligence, formerly known as MDI. Before we dive in, we have a couple of technical notes for you. Number one for audio issues, audio is through ÃÛ¶¹ÊÓƵ Connect. So your speakers or headphones must be unmuted and then ensure the speaker icon is on at the top of the Kinect room. We don’t currently have an option for calling in via phone. It doesn’t always work well with Bluetooth headphones, so if you’re using those you can try switching to wired headphones. If you’re having an issue. You can also try logging out of the room and back in or switching to the desktop app instead of the browser version. And number two, throughout the webinar, if you face any technical issues with the audio or the screen share, or if you have questions related to the functionality of ÃÛ¶¹ÊÓƵ Commerce Intelligence or related to the content being presented, please feel free to put those questions in the Q&A pod at the left of your screen and we’ll be monitoring that. While the recording of today’s content plays. We will try to answer those questions either right away through the chat or during our Q&A segment at the end of the webinar. And finally, we will be sending out a link to a recording of the webinar afterward. All right. Now I’ll hand it over to Deepak. Thank you for joining this webinar. In this session, we will try and cover the lifecycle of data. It will be Commerce, Intelligence. We will start with a brief introduction, followed by different ways of importing data into commerce, Intelligence, configure data, warehouse set of data transformations using calculated columns, column parts, views, etc… Once our data warehouse is ready with necessary data and transformations, we will create a business intelligence report that uses data coming from ÃÛ¶¹ÊÓƵ Commerce and Google Analytics. For we will look at exporting data from. It’ll become intelligence towards the end of the session. We will have a Q&A segment where we will answer any questions you may have on this topic within our comms intelligence ecosystem. Today, we will focus at the admin user activities related to data lifecycle. Further, we will create a report and associated to an existing dashboard. For more information on our almost intelligence ecosystem, you can refer to one of our previous webinars called Getting Started with ÃÛ¶¹ÊÓƵ Commons Intelligence. Let us understand the lifecycle of data in ÃÛ¶¹ÊÓƵ Commerce Intelligence. Call US intelligence broadly has data warehousing component where data from different sources could be imported. All the basic features of managing this data warehouse are provided. If you are and you do become this customer, then this data warehouse becomes pre integrated with its MySchool database. Then there is a business intelligence component that utilizes the data and transformations from data warehouse to build reports. These reports provide key insights to the merchants on how their business is performing and helps them take important decisions. Data can be replicated from different solar systems. These are broadly categorized as database API integration, CSP, upload and import API. A data pipeline can be created using databases from my school, both grade school and school server. Amazon Redshift Commerce Intelligence allows API integration with ÃÛ¶¹ÊÓƵ Analytics, Google Analytics, Facebook to name a few. The list here is subject to change based on some new integrations or existing integrations. Getting deprecated, you can directly upload your data in a simple CSP format. This helps you to bring any tabular data in our data warehouse for storage, transformation and reporting purposes. If you have members well-versed in API integration, cost intelligence provides import APIs so you can build a data pipeline. Please note CSP upload and import API are not chargeable for use as the API integrations listed here are available. Free. If you have a pro license, please contact our CSM team for more details. Data can be exported from Commerce Intelligence, either in file formats like CSP or Excel as our true Export API documentation for Import API and Export API can easily be found in our online help. With this, we will now move to a live team. Let us understand how to import data. In comes intelligence. Go to manage data integration. Here you can find a list of all the existing integrations and an option to add integration for each of the existing integrations. We have an option to edit or delete. Let us see what options are given in ADD integration. This page shows all possible integrations broadly categorized as available integrations, standard integrations and premium integrations. As the name suggests, available integrations are a list of free integrations, as well as the other integrations a given customer is entitled as per his license agreement. Standard integrations include a list of databases and SAS applications. If you are a pro license holder, some of these will be allowed free of cost. Please contact your customer success team for details. Premium integrations are the ones that are always chargeable for demo purposes. I will try and add a Google Analytics for Life integration. Remember, Google has recently deprecated its Universal Analytics or J3. This is a flawed version. Click on this Google Analytics icon. Choose the analytics account from the Google Popup. As soon as we add the account, we will be redirected to Commerce Intelligence page with a list of DB profiles within this account. Choose the profile to track. You will see this confirmation. Now let us go to the list of integrations. We now see a new integration here. Google Analytics Ford, along with its GM Ford account and property name ÃÛ¶¹ÊÓƵ Narratives, is a popular analytics platform like Google Analytics. It gives you the user behavior insights for your e-commerce storefront with a white list of metrics and dimensions to add a new integration. Click on it will be analytics icon. Click address with ÃÛ¶¹ÊÓƵ in an index and other username and password. After successful authorization, you will be redirected to Commerce Intelligence interface where you need to select one of the report suites and click on Continue from the resulting page. We need to select the metrics and dimension. This system allows the combination of 25 metrics and dimensions. I will select page views and bounce rate with a dimension related to date and click on. Okay. Save Integration. This is going to create a data warehouse table name. Then you can see the success message. Click on Integrations again to check whether the newly created ÃÛ¶¹ÊÓƵ Analytics integration is visible. In addition to SAS DBA integrations. If there is any data available in CSP format, it can easily be imported to our data warehouse. To do that, click on file uploads. Choose file for demo purpose. I kept a list of country codes that names and population ready with me. It will validate the file for any discrepancies and then list the column names and suggested data type. Specify the table name. A column needs to be specified as a primary key. Click on same table. Now let us check whether it is visible in our data warehouse. Go to data warehouse and file uploads. You can see the newly created table. With this we are done with the data input in our demo today. We will make use of data coming from ÃÛ¶¹ÊÓƵ Commerce and Google Analytics for integration to build reports. Now let us configure our data warehouse to suit our business needs. Commerce Intelligence provides an intuitive interface to perform all the basic settings to set up and tweak your data warehouse. Please note this feature is available for users with a window. Navigate to manage data Data warehouse. This page shows a list of tables that are synchronized by default. You can toggle between these tabs to see a list of all the tables with a synchronized with ruby commas intelligence or not. There is an option to expand or collapse the tables or views arranged by the integration name. For example, main generator is ÃÛ¶¹ÊÓƵ Commas. My Ezekial DB integration, whereas file uploads is a group of all the CSB files uploaded and this is a data warehouse view. This option runs a structured sync to see if any new tables were created. It updates a data warehouse with the same starting from the top. There is an option to view last successful data update view update status along with an option to email you once the update is completed. If no update is in progress, you can initiate a forced update from here on need basis. Adding can change his time zone accordingly, the data updates get impacted. This is the currently selected table name preceded by its database name. The will icon allows you to export table data from the selected table. Start a synchronization from selected table. Please note the check for new tables and columns is a structure sync and sync Now is for data sync. Drop table will check for any dependencies whether this table is being used in any metrics, reports, dashboards, etc. It would be a wise option not to try this without removing its dependencies as the action is not reversible for a given table. There is a replication method displayed clicking on it shows a pop up to configure the replication method. Incremental replication is an efficient way of reducing the application cycle time. This is because commerce, intelligence only points at the changes related to new or updated data within a table. Full table replication method helps in case of any noodles detected as so stable. It does not look for any data changes in existing rows of your data warehouse. Hence, it is not as efficient as incremental replication in terms of change of existing data. For more information on replication methods, please refer to our webinar Optimize your data warehouse. We have two tabs column settings and data preview as the name suggests. Column settings allows you to view the column names and the type specification. Data Preview shows a sample data from the selected table. Column settings for a given table has a few notable features for each field. We can see either a green tick icon or gray block icon or three blue dots at any time. Green tick means the field is part of table synchronization. Great block icon means a given field is not being synchronized for demo purposes. I will select this field. Click on the Sync button. Now we can see three blue dots. That means the next update cycle will start letting this field from source to synchronized into our data warehouse. Let us take a look at the calculated columns. The fields would show a blue edit icon mean they are calculated columns within our data warehouse. These columns act like an extension to the existing list of columns in a given table that can apply complex calculations and joins with other tables. So there are the list of native columns inside this table, whereas these are the calculated columns. I kept a calculated column ready for our baby. Not to worry. This is called customer’s Lifetime Number of Orders. Let me show the details of Calculated column to understand the settings better. First, we specify the column definition, whether it is within the same table or one too many or many to one. In our case, my current table is customer entity. I want to point at sales order to count for the number of orders a given customer has placed. So I will choose my need to one Specify column definition as count. Select the sortable join using column parts. We will cover column, but a little later. This many to one selection appears suitable for my calculated column requirement. If not available, please navigate to column parts and create a new one. We will look at creation of column parts and their utilization in our data warehouse. Additionally, I can apply filters that I created to have all the relevant orders me count. Likewise, if I want to have a calculated column for customers lifetime revenue, I will choose my column definition as some select the suitable column part and select the revenue related fee based grand total. This was a demonstration of how calculated columns can be created in advance so that the same can be used as a group by dimension during report creation. Similarly, I also have another calculated column which I’m going to be using for my report Creation today. There could be other use cases of calculated columns like order event sequentially, or find the time between two events, compare sequential event values, convert currency, convert time zones, or any custom calculation using Postgres SKU syntax. Moving back to the configurations for columns in a table, you can apply recheck frequency and specify a time. Set a given field as primary key or change the field type to one of these. For example, if there is a revenue related field, I might want it to be depicted in my report. Preceded with a currency symbol. If a calculated column depicts a percentage calculation, I might want it to be suitably affixed with a percentage symbol and so forth. You must have noticed usage of column part while covering the calculated columns topic. Let us understand the feature a bit more. The column part functionality in commas. Intelligence is a common place where all the relationships are joints between tables. Within the data warehouse can be established. You can join two tables based on minute one or 1 to 1 relationship using the primary and foreign keys. Once created, they can be used multiple times during creation of calculated columns for your business. If you are an existing customer of ÃÛ¶¹ÊÓƵ Commas, you can expect automatic column parts being created out of the box for you from day one. Now let’s switch to our next topic. Data Warehouse Views. Data warehouse views helps us to create new tables within our data warehouse using existing tables. Some of the benefits include data security, so various data security policies can be applied to ensure restricted access is given to highly sensitive data. Apart from that, data warehouse views enable data across multiple tables to be viewed at one place. Data warehouse views can help improve equity performance by pre computing and storing the results of complex queries instead of executing complex queries every time. Users can query the view, which retrieves the pre calculated results leading to faster response times. I created a sample data warehouse view for demo purpose. As you can see, it has a select statement with PostgreSQL syntax. The same can be viewed in data warehouse. It can also be utilized in creation of column bots. The data warehouse views can also be utilized in creation of 3 to 6, and we can make use of them during creation of metrics as well. Let us create a report which makes use of data coming from ÃÛ¶¹ÊÓƵ Commons and Google Analytics. Assuming that I opened a brand new online store trunk during the month of April and May last year and started a limited edition iPhone product launch during that time. So I want to create a report to compare the bulk orders with customers Lifetime number of orders is greater than 50, and I also want to see the page views of the store front coming from Google Analytics during that period. So in order to create the report that is click on Report Builder, Visual Report Builder. Let us add a metric called Orders and filter it by customer’s lifetime number of orders greater than 50. Please note this is one of the calculated columns we created to meet this requirement. You can now realize the power of having such calculated columns for insights into business. Filter the date for April and May 20, 23. Nonreaders. Add a metric from Google Analytics like Indignation. Click on this integration We newly added during the beginning of the session and select page views. You can also see these are a list of all the remaining metrics we received from Google Analytics for Please remember this is demo data, so the final report may not be too realistic. Change the report view as horizontal bar. Chuck Overall, we can understand from this report that the bulk orders placed during April were better than the month of me with lesser page views. It reflects the customer sentiments to buy the flashy limited edition iPhone sooner than later. Let us save this report in a new dashboard. With this, we are done with the use case where we can effectively use our integrations and data warehouse configurations to derive business insights. Exporting data is the last part of our data lifecycle. In this section, we will cover exporting data from commerce Intelligence. Data export for reports is available for all users of commerce intelligence, regardless of their permissions. In order to download the underlying data from the report, let us click on the gear icon Report Export It exports the data in CSP format up to 3500 rows full. CSP export allows the user to download in CSP for Mac this time ranging the data up to 1 billion rows full. CSP export doesn’t seem for reports which have data ranging up to 1 million rooms. Full Excel export is the same as the above option, except that the file format is Excel as x. A simple report like this usually has very less data points to be exported. Hence the first option is suitable. However, there might be cases where reports being viewed has many more data points which may exceed 2500. So let me navigate to one of the tabular reports, which has too many data points. This is for demo purposes to view high volume of data points into ports. After downloading, now we can see the tabular report having a lot more rows of data. So far we saw exporting of data from reports that is processed. However, there may be requirement to download the raw data stored in our data warehouse, which may have master as well as transaction data stored within. Raw data can be exported in two ways from reports in a given dashboard and another from dedicated raw export option from manage data. Let us start with a raw data export from a report. The new raw data export public opens with native columns that are available from the table and native columns based on which the report was generated. We can add or remove any columns based on the business need. For this demo I’m going to add all the columns one shot using at all. Optionally, we can filter the exported data based on a condition. Once they are ready, click on export data. This action does a job in Commerce intelligence. Let us view the job details and download the exported data. Once we are done with the initiation of raw data export. Now let us take a look at how to download the data. As we know, the download of the data is so very important it has only been provided to users with admin axes. To do this, we need to navigate to manage data raw data on the left pane. As you can notice, even though a raw data export can be initiated by any user, in comes intelligence, only a user with admin rights would be able to view the raw data and download it. This page shows a list of raw data export initiated for the last one week. It is a unique number given by Commerce intelligence to each the raw data export. Name is the user defined name given by user. During export we can see the raw count of exported data timestamp when export was initiated by user expiry date. After a week from now, discarded export will be automatically deleted. Export definition helps us with a quick view of the table, its columns and any filter condition specified during creation and click of this button. I can download a zip file that contains the raw data exported in six weeks. Let us take a quick look at the CSB file. We can see all the native columns of the table and rows of data running to a few thousands. In this case. Moving further, we can also initiate a new raw data export from this page using an export button and click of new raw data export. The pop up opens. This pop up is the same as the one we launched from reports. In this case, the user has to start from scratch. Select a table its associated columns, specify the condition if required, and click on export data. I’m canceling this option for now. As we tried the same earlier, raw data export is different from CSB or Excel as export in many ways. Report export in CSP excellence format. Allow native columns, calculated columns and multiple metrics being used during creation of reports, whereas raw data export can bring in only native columns. Report export in CSP or Exelis format has a size limitation of 1 million records, whereas the raw data export allows a maximum of 10 million records. Please remember the raw export option and Commerce Intelligence will be disabled for reports in three cases. One is a report that contains more than one metric. Another case is reports created using a skilled report reader. The third case is reports containing formulas. Exporting raw data enables data analysts to obtain backend data from commerce Intelligence data warehouse. This helps the data analysts to identify any data discrepancy between sold systems and commerce. Intelligence. It also helps the data analysts to use this for any downstream report generation or data integration. For any additional information on the topics covered in our webinar. Please visit our online help or reach out to our support team. Thank you. All right. Thank you for that great demo. Let’s get on from there. All right. Let’s move on to the Q&A portion. Please submit any additional questions that you may have in the Q&A pod. On the left side of your screen also, please submit your feedback in the poll. Questions now showing on your screen. These are really helpful for us to improve our content in the future. If you have questions after the webinar or if we don’t get to your question during the Q&A, please feel free to send an email to MBI webinar at ÃÛ¶¹ÊÓƵ dot com and we’ll receive questions sent there for about the next week. As a reminder, you will get a follow up email in the next day or two with a link to a recording of this webinar and a link to the recordings of our other webinars on experience league, as well as the email address that I just mentioned. You may also be interested in our Walk Through Course now available through ÃÛ¶¹ÊÓƵ. Excuse me. ÃÛ¶¹ÊÓƵ Digital Learning Services. You can find out more about that course Learning dot ÃÛ¶¹ÊÓƵ dot com. All right, let’s see what we’ve got here. First question. Is there a limit on how many integrations we can add? Yeah, there is no technical limitation as such, but how many integrations you can add to an account also depends on your contract. So most of the Commerce Intelligence pro accounts come with almost around five and eight level integrations and you can add any number of open API connections for CSP uploads you like to. If you want to add more standard or premium integrations, you can do a monthly subscription. Once the data is available in commerce intelligence. It doesn’t really make a difference which source the data in a report is coming from, because all the data is in a single data warehouse. So there is no technical limitation to how many sources you can join together in a single report. Okay. Thank you. Our next question says once I set up a new integration or column, can I share it with everyone in my organization? Or do they also have to set up their own? Yeah, that’s a good question. Anytime you create a new column or metric, it’s automatically shared across your organization. Any I wouldn’t use it in your account can see those columns and also make changes to those columns, making it easier to ensure everyone has access to the same columns and data for building and then reports. However, you do have the ability to limit which standard users you want access for each meeting. Okay. Thank you. Next we have, if I think, another column in one of my new tables after this sync of the table, will it be automatically added as a group of all dimension to my metrics? Yeah, this actually depends on a couple of things. Whenever using a new native column, I create a new calculated column, you’ll have to go and you have to add it manually as a dimension on any existing metrics before you. You can filter a group by individual reports. And this works the same way as we went through when we created the New calculated column and then added it as a group or dimension to some of the metrics. You know, however, if you if you think a new field or create a new column and then create a new metric after the new column exists, Commerce Intelligence may not make some decisions on which columns to include as visitors are group based. So depending on the data type of your new field, it you might want to decide this is this would probably be a good free for a feature and then add it automatically. So if it is not added automatically, you can go into the metric edit page and add it yourself manually. Thanks. Just a really quick I think you maybe kind of stumbled to your words just a moment. I think you meant to say does in ÃÛ¶¹ÊÓƵ Commerce Intelligence does make some decisions about it on on its own and then you can go and edit those later as you actually mentions. Yeah. Yeah. Make sure we see it clearly for everybody. Yeah. So our next question here is, is there any data storage limit? There is no hard limit on data storage, but you may have noticed on the integrations page, there are different tiers of integration. There are some integrations that tend to have a lot more data like the Redshift or Salesforce, whereas there are other premium integrations where, although it costs a bit more, you know, to add them into the monthly monthly contract. But in terms of the data limits for given integration, there is no particular limit on what all you may run across is when importing a CSB or using the import API. There are a couple of rate limits in place for how much you can bring in to comments commerce, intelligence at one time. But there is no overall limit on the number of size of tables. So you should keep in mind though, that more data you import, the longer your updates may take. As mentioned during the demo, you should make sure you bring in just the data you need for your analysis goals. Okay. Our next question here is when I look at my data warehouse, I only see a few tables from my commerce database. How can I think data from a table that isn’t in the list? Yeah, we newcomer’s intelligence account is is set up for the first time on a standard commerce database. The processes that run automatically think a new set of tables with most useful data for many of our customers. So if you only see around eight or so tables in the all Tables tab of your data warehouse, you would like to replicate data from additional tables. You can add those other to your list by clicking on the data warehouse where it says Check for new tables and columns. So this will lead to the full set of tables from your commerce DV showing in the data warehouse. All tables that note that process that takes a little while running depends on how many new tables are getting picked up. So clicking on check for new tables and columns is also what you can do if you can. If you want to make a change to the structure of a table that is already listed to get commerce Intelligence to pick up add column. So you can think I know that this does not apply to all single data sources. You can decide you only want to list all the tables from your commerce DV and not from some other connected data source. So you can submit a support ticker to get more information on scenarios like this. All right. I think we have time for maybe one, maybe two more questions here. We’ve got have a Commerce Intelligence pro license. And although I have a G for a Google Analytics floor account set up in Google, I am not yet. I don’t yet have it set up in commerce intelligence. I guess when it’s when I set it up, will this integration, such all of the historical data that I have in my A4 accounts or I guess, or will it only start retrieving data sort of at the time that it gets set up? So which one of those is the right behavior, the expected behavior? Yeah, that’s a great question. In scenarios like days where where our customers have moved on with Google Analytics for the historic data of the G4 for data will be visible as per your time limit. So whatever you have set up in your Google Analytics account. I think there is a time limit around 12 to 24 months. So the same thing applies whatever you have set up in your G4 account and you know, as soon as you create, maybe even it could be yesterday, August, a few months ago, as soon as you add a new G4 integration into ÃÛ¶¹ÊÓƵ Commerce Intelligence, you will be able to see the entire 12 months, 24 months, whatever you have stack up in your Google. Great. Yeah. And then also just add on to that, unless you set up your some some additional processes, ÃÛ¶¹ÊÓƵ Commerce Intelligence will hold on to that historical data as it gathers it. So it won’t be subject to the same deletion as the Google Analytics unless you set it up so that the the replication will account for that. So be aware of that. If you have restrictions on how long you can hold that data. But also if you need to hold that data longer, then that may be an option to do as well. All right. And we are at time we want to make this a 45 minute webinar here. So apologies if we weren’t able to get to your question, but thank you very much for joining us today. Again, if you have questions you wanted answered that we weren’t able to get to, we will be sending out a follow up email with an address for you to send those to if you would like, and we recording links. So we really hope that you got some useful information out today’s session and have a great rest of your day.