Google Data Studio

Google Data Studio
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Google Data Studio is a facility provided by Google to users. It is a free tool that is provided by Google to the users who are wanted to make their custom reports from the Google Marketing source and other external sources where we have the data to make a report. Data Studio acts as Google’s reporting solution for the power users who are wanted to go beyond the data and work on the dashboards of Google Analytics. There are some widgets that we can find in the data studio. These data widgets in the Data Studio are recognized and notable for their variety, users’ customized options, live data which means the data will be updated for time to time intervals so that the data will be fresh at the time of our usage, and interactive controls. Under interactive controls, there are a variety of things such as column sorting which will help the data to be in the order the column-wise to look the data in a neat and arranged manner and table pagination. Table pagination is a simple navigation method that will help the users to split the huge amount of data contents within the tables and divide the content into smaller table formats that are easy to understand by the users and for the readers also. By default, pagination is initialized and designed with the previous, page numbers and next buttons which are very useful for the users. Data sources will also include Google products like analytics, Adwords, search console, sheets, youtube, etc., data connectors; file upload, and ‘community connectors for making the popular marketing services.

Google Data Studio has started not started directly into the market but it has taken a part in the enterprise Google Analytics 360 suite. Soon after then in May 2016, Google has made an evolutionary decision and announced that they release a free version of data studio for the individuals who wanted to start making the report on their own and for the smaller teams who wanted to make a report can find an easy way by using this Google Studio. At the time Google has launched this Google Studio in two different formats one is for free and this version is completely for the users and for the paid version we need to make the payment to the advanced Google Data Studio, such as the number of reports that could be created per the account is different.

By February 2017, Google has removed the paid version of the Studio and announced it for free and the users or the smaller teams can make the unlimited studio report based upon the one interest. So from February 2017, the free version of the Google Studio reports are available throughout this world and added some powerful features and made some changes for the usability enhancements. So we need to thank Google Data Studio because we can now be able to communicate and act on the customized data. The main use of this customized data is that we can get all the required information as speedily as possible and there is no need for checking out other websites or data sources, simply we can get the required data directly from the report which will be provided by the Google Data Studio. Many members are working under this Google Data Studio who are busy emphasizing the data for the users.
The people who work under this Google Data Studio like developers, execs, and global team members who work for the different departments can compare the data and they add filters to the data, and can organize the exact data that they want to add to the single report. By using this Google Data Studio there is a lot of timing saving for the users who don’t want to browse for different websites for the information and they can get all the required data in one single report. Not only they can get the information but also they can prepare their information of their own and can set it in one single report and can make more reports which will depend on the one’s interest. Data Studio works seamlessly with other solutions, allowing us to access the data from one product while we are working with another. This goanna saves a lot of time and helps us to develop the data increasingly efficiently. Our marketing dashboards can be very easy to use but when we have a platform that allows us to do it in that way. Well to do that the Google Data Studio has set a platform so that we can do whatever we wanted to do and we can run the marketing dashboards as well. We all have cache on mobile devices. If that cache expires, or if we get any query that cannot be served in the cache that is present in the device, then the data studio will go to your data and get the data from it. There is a chance that we can avoid these potentially slow data fetches by extracting the data up to 100MB of the existing data source into the data from which we gonna extract from. We all have sometimes observed that there is a loading error while we are using the device; the reason behind this is Google Studio.
Google Data Studio dashboards can take some sweet time to load. The reason behind the slow load time is that the data studio is fetching a large amount or large volume of data directly from the original data source. So the main key work that the Google Extract Data connector does is that it extracts and store data from the source before we are using the reports. This will help us to give the freshest data without facing the problem of load times. So when we are using the Supermetrics for Data Studio, we are having a benefit that we can enjoy some of the advantages of data warehouse solution without any of the costs, commitments, or any other technical complications.

• There is a large advantage that we can link the Supermetrics data source with the Google Extract Data connector and we can select the field which we want to use in our report.

• Then the connector will start its work. The connector will extract and will store the extracted data or stored data and this data will be updated at a set of time intervals.

• Here the key role plays by the Data Studio. This Data Studio uses the stored data than taking the live data from the data source. This will make our reports load much faster time compared to the original time taken.

• It is customer friendly and we can the total control over the data that is stored, and we can delete the stored data by deleting the Extract Data source at any time and a given set of points.

We are having a large number of advantages of using Extract Data Connector. Some of the main advantages are listed below:-
 The main advantage of the extract data connector is that we get a faster loading time. There are two types of data one is extracted data and another one is fetching data. Extracted data is the data that is extracted directly from the data source and fetching data is the data that is going to search and shown in the report. So by using the extracted data the load time is very low because we will extract the data directly from the data source so we will get the data executed in the report as fast as possible.

 We get more responsive reports because very little data is moved around which will make our calculations easier and faster. The reports will also respond to the filters which are present inside the extract data connector and makes the other changes quicker and can complete the report as fast as possible.

 It is free to use. That means we can extract the data connector when we are in the need to increase the speed and can use the direct data source connectors when we need to increase the flexibility. We can also use the direct source connectors when we gonna go for the deeper search analysis.

 We have total control over the stored data. This means the data that flows from the data source to the Google Data Studio is just like direct connections. The only thing is that when the fields we are going to select are extracted and stored, and this stored data will going to delete when you will delete the Extract Data Source.
Steps for setting up the Extract Data Connector:-

 The first basic step for setting up and configure the extract data connector is that we need to select the Supermetrics connector. After selecting the connector which we want to use than by using that connector we need to extract the data. After extracting the data by using the Supermetrics connector we need to set the connection parameters after setting up the parameters of the collection we need to click on ‘connect’. After clicking on the connect option it will check whether we have given the right parameters or not. Then the Extract Data Connector works with all the connectors which we have given to it and moves to the further step for setting up of Extract Data Connector.

 After the extract data connector works with all the connectors then we move on to this step where we gonna add the Extract Data connector to the report which was made by us. To do this, we need to set our Supermetrics connection after the setup we need to link this Supermetrics connection with the Extract Data Connector. We can find this Extract data connector or it is available on the internet where we need to go to into the connector gallery which is under the name of ‘Google connectors’ after browsing it, we will get the required extract data connector. Soon after the completion of the connector, we need to add the Extract Data Connector to our report which was made by us.

 The further step we need to do is that we need to link with a Supermetrics data source to the Extract data source. To do this step we need to make sure that after setting up the Extract Data connector, firstly we need to select the Supermetrics data source that was created in the starting step of the Extract data connector.
 The key and the main step have arrived. In this step, we need to select the data that we need or want to extract and to make sure when to update it. To do this step we need to add or select the metrics and dimensions that we need to add in our report to show more available information that we need to show It in our report. Metrics and dimensions are not compulsory needed to add in the report it depends on one’s interest.

 After selecting the Metrics and dimensions that we need to add to our report, now we need to select the data range in which our data will get stored in the given date range. Once the data arrangement has been set to our report, now we need to focus on the filters that are needed to set up for the Data and need to select or add the possible filters to the data once the data range has been set to the data. The further step that we need to proceed with is that we need to turn on the ‘Auto Update’ option so that our report will be got updated in the time intervals and will be fresh at the time of our use.

 Once the auto-update is turned on we need to select the frequency range for our data that we want our data to be preloaded to the storage. Once we are sure that we have made all the required settings and options we need to click on the ‘Save’ option, once the data is saved we need to click on the ‘Extract’ option so that our data is saved and extracted simultaneously.

 After setting up all the contents that are said in the above steps, now our Extract Data connector will become a stronger connector which means that we can use the Extract Data connector like any other connector.
 The fields that are available in the report and the data range that we have set before are based on what we have selected before setting up the connector so that it gives us the information about the required field that we want to choose in the connector.

 The data must need to be updated between time to the time interval and the process of updating is done automatically from the data source based on the update frequency we have selected before setting up the connector.

Usage of Extract Data Connector:-

• There are many uses of Extract Data connectors. The main role that Extract Data Connector does is that it will give us a speedy report which will gonna save our time and it will provide us with a limited number of fields. This data connector is best suitable for reporting on a limited set of matrices that we need regularly. For example, we can use this data connector for our standard marketing dashboards which will include a fixed set of KPIs and it will take a fixed amount of time.

• There are many reports we can make and analyze. In the case of ad hoc reports and analysis, we need to choose the direct data source connectors rather than using other connectors since they provide us with more freedom so that we can explore to make an analysis. We can also combine both Extract data connectors and live connections in the same report and analysis so that we can get the best result by combining these two connectors in the single report and analysis and are the best of their two own worlds

Limitations of using Extract Data Connector:-

 There will be a fixed subset of data is available. The problem that we are going to face with it is that there are only preselected fields and a limited range of data is available. But for the benefits of the users or customers, they have given an option to add more fields which means that we can add more fields to the Extract Data Connector if we want to increase or have a need to add the fields.

 The data which we are going to use is not live but it will be refreshed. This means the data will not be permanent that we are going to assign it, but we have the efficiency and capability to change the data and add more to it. Also, this data will be refreshed at some set of intervals of time and make the data fresh.

 The main requirement to store the data is that we need to have a specified amount of space to store the data. In extract data connector we will be having 100MB of storage to store our data which is more enough or sufficient for our daily report analysis. This storage space can be increased we need granular data for doing deeper analysis because 100MB storage cannot be able to store the data for the deeper analysis. To increase the storage capacity to do a deeper analysis, a data warehouse is the best way to go.

Data dashboarding:-

 Using data dashboarding we can be able to unite our data from spreadsheets, Analytics, Google ads, Google Big Query, and more.

 By using this data dashboarding we can also be able to explore the data. This will transform our raw data into the metrics and dimensions that are needed to create easy-to-understand reports and dashboards and there are no code or queries that are required.

 We can also create and tell impactful stories. By using this we can create the stories and also share engaging reports and data visualizations that will tell us the story.

 There is a chance that we can also empower our teams. Arm people with the knowledge of your key metrics by sharing the automated data dashboards which mean that the data will be going to update automatically and will be updated between time to time intervals and it will focus more on what the content matters.

Google has made an evolutionary step to set up the Google Data Studio which has made so many changes in the present day scenario. This Google Data Studio has given us a vast number of uses that there is no need for searching different types of websites for knowing the information about the data which we have but rather we can go directly to the report and check whatever information needed and analyze it. This will save our time more efficiently and get valuable information and not only in this way we can also create our report and work on it. Google Data Studio plays a very important role in the marketing dashboards because it will save us a lot of time and can prepare our report on it. In this way, data dashboarding will also play a very important role in this field. It will help us to unite all the data in one place, helps to explore the data and can get more information, it will tell impactful stories, it will empower our teams which means that the data which is present in the report will be updated automatically and will be up to the data at the time of our use. Lastly, we all need to thank Google for providing us with the Google Data Studio so that we can communicate and act on the customized data.

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