data strategy

Making Klipfolio a Fitting Piece of Your Existing IT Puzzle

What are the data handling limitations that come with Klipfolio?

Klipfolio is beside Tableau, Zoho Analytics and Google Data Studio as one of the most popular data visualization tools on the market today. We can say that it is in the top 10 software players in this segment in 2019.

Klipfolio’s main focus is on data visualization and they offer a powerful solution. But while visualization is great, it’s only the end result of the data puzzle. Your data has to come a long way from measuring, collecting, consolidation, preparation and then final output to your visualization tool for interpretation. In order to generate aesthetically pleasing, all-inclusive reports for your team members or clients, one must navigate each step in the data handling process which can be rather time consuming. 

So what are some of the issues you have to solve when working with a visualization tool and how should you deal with them? The answer is a no-code data integration platform capable of automating and simplifying your company data journey without the need for external developers and additional costs. Dataddo can connect all of your data with your BI tools, dashboarding apps and data storage solutions and you don’t need to write a single line of code.

Although Klipfolio provides somewhat universal connectors to CSV or JSON data, there are multiple cases when this solution cannot be used:

  • An increasing number of APIs utilize the OAuth 2.0 authorization scheme. The lack of a generic OAuth2 authorizer prohibits connection to such services.
  • Some APIs must perform multiple calls to obtain the desired result. E.g. number of results per single call is limited, so it is necessary to traverse using workarounds or to work with dynamically generated cursors.
  • Many APIs require the use of dynamic parameters produced as results of a different call, like using one call to get all Users IDS and then dynamically “emitting” a call for each User to obtain details.

With a growing number of data sources that companies need to connect to and ever- changing data handling needs, it’s important to have an infrastructure in place that is as flexible as possible. Additionally, your data management has to stand on a solid foundation, on a data pipeline that connects all of your data sources, all of your online services and all of your data destinations. The entire process should be so seamless, simple and flexible that you forget that you are even using a data handling pipeline. That’s the value that Dataddo can bring to your company’s data management infrastructure.

data strategy

Zoho Analytics + Dataddo – A Complete Data Analytics Package

Zoho Analytics is a powerful tool for reporting and analytics, however it can be difficult to aggregate data from the seemingly endless list of data sources that companies need to deal with and send it to dashboards.  

With Dataddo’s data integration platform, organizations can extract, prep and send any data to Zoho Analytics automatically at set intervals without writing a single line of code. Dataddo offers native connectors to a wide variety of popular online services and can connect to almost any service with an API using our JSON, XML, CSV or community connectors. 

Dataddo eliminates the need for extensive ETL engineering and automates data handling processes so your team can focus on drawing new insights from analytics data instead of wasting time dealing with data preparation.  

Dataddo offers a two week free trial of our platform so that you can connect your various data sources and test the output to Zoho Analytics using our native connector. If you need assistance configuring the platform, feel free to contact us and we will get you in touch with one of our data integration specialists!

data strategy

Why should a no-code data integration platform be considered a critical component for data fabric?

The advent of the internet, social networks, real-time analytics tools and artificial intelligence are profoundly changing almost every business process towards being data-driven, fostering almost ‘scientific’ approaches to business management. Indeed, this creates a considerable reliance not just on the data itself, but on the underlying data infrastructure as well. Since non-technical departments such as marketing or sales often tend to be primary drivers of this shift, the underlying infrastructure has to reflect the fact that it’s operators typically do not have a degree in computer science.

‘Shadow IT’ fostering siloed analytics within organizations

Arguably the most crucial factor of changes in the modern business environment is the availability of real-time (or near real-time) data to make qualified business decisions. 20 years ago, it was pretty common to conduct research in the form of financial analyses, focus groups, questionnaires or marketing studies prior to each critical decision. The issue with these practices is that they were often rather occasional and performed on a small scale, therefore past experiences of business leaders and their ‘gut feelings’ were essential ingredients of the decision-making process. With the advent of digital products, online customer-facing systems and digital sales channels, there is a vast surplus of various analytics tools that can provide unprecedented insights. However, the adoption of these tools and services (mostly delivered as SaaS) was usually not driven by the overall IT strategy, but rather end-users creating what some call the phenomenon of shadow IT. Since many services such as Salesforce, Zendesk or Google Analytics gradually grew into enterprise-grade softwares, organizations usually built siloed teams and capabilities on top these systems.

Data integration platform as the centerpiece of data fabric

Adoption of data analytics within organizations naturally forces the centralization of analytics capabilities since the previously mentioned siloed architecture is rather expensive and creates frictions between internal teams and departments. In support of this claim, renowned IT analytics and research firm Gartner identified data fabric as one of the critical data and analytics trends. According to Gartner, “Data fabric enables frictionless access and sharing of data in a distributed data environment. It enables a single and consistent data management framework, which allows seamless data access and processing by design across otherwise siloed storage.” Since data experts find it extremely painful to work with analytics data from multiple web, social, sales or customer platforms, we developed the Dataddo integration platform that helps our customers to centralize all their analytics data into a single point; whether it is a dashboarding app like Tableau or Google Data Studio, their data-warehouse or cloud-based big data storage.

No-code platforms as an answer to increasing demand for technical skills in non-technical departments

The trend of proliferation of data analytics in the organisations result in another outcome; increasing requirements on non-technical employees (usually in marketing, product or sales) to deal with tasks previously dominated by people with a technical skill set such as data-prep scripting, SQL or data architecture. Indeed, it is not uncommon that basic knowledge of coding and working knowledge of technology is often considered as one of must-have skills for marketers. However, marketers are not coders and vice versa, therefore it is important to provide the non-technical staff with tools and platform, allowing them to perform complex operations, but still having ‘human’ interface. Therefore the no-code / low-code platform is the answer for solving this issue.

data strategy

Data dispersity, the next big challenge for data-driven organizations

A clear trend in today’s business IT is the proliferation of various cloud-based services that seek to lower operational costs, facilitate the adoption of new technologies and improve overall business performance. It has become common practice for businesses to use CRM for clients and lead management, business intelligence tools for financial analysis, Google Analytics to track online channel performance, Google AdWords for online campaign management and the list goes on. Having immediate access to performance information regarding various aspects of your business is always great. However, this is easier said than done. With and abundance of data coming from these services and with new tools and services appearing all the time, orchestrating the entire infrastructure for your organization’s data ecosystem can be a daunting task. To make things worse, many of these services don’t integrate with each other out of the box, creating major headaches for data analysts who want to look at the bigger picture regarding their company’s data. Businesses generally address this issue either by hiring staff to operate the various platforms independently, (The Login>Select>Filter>Download>Process-in-spreadsheet routine) or by paying for the costly custom development of various data bridges which can be chaotic and expensive as data sources from new services are continuously added to the ecosystem.

Businesses Crave Automation and Truly Seamless Data Integration

Dataddo is a universal analytics, advertising and customer data pipeline allowing data integration, automation and transformation. Our platform is designed to work with almost any online data service and already covers existing popular analytics platforms, CRMs, adtech solutions and social networks. Dataddo transforms and wires data to a wide range of databases, DWHs, cloud storages and dashboarding/BI applications allowing for smooth and simple integration with your existing IT and BI stacks. Dataddo creates simplicity for organizations in the expanding and increasingly chaotic data analytics ecosystem.

Openness and Flexibility are Crucial

We believe that the ever-growing dispersity of online data sources will eventually force most companies with considerable internet activities to deploy a data integration solution. We built Dataddo with openness and flexibility as our core driving concepts, leading to a solution that works even for organizations with legacy systems or proprietary solutions.

It is Not Just About Software

At Dataddo, we are all data-crazy. This mentality helps us understand the importance of being effective and efficient when it comes to working with data. Our mission is to help our clients use the ever-growing amount of data to their advantage rather than having it complicate things. For example, one of our clients is of the largest marketing agencies in the EU and they manage hundreds of Facebook, Instagram and Google campaigns on behalf of their clients. In the past, it would take two analysts and 4 full days of work at the beginning of each month to create performance reports for their various campaigns. The chain of tasks ranging from obtaining the data itself, through data transformation, to delivery to the client’s endpoints was automated by Dataddo saving them dozens of hours each month and obviously quite a bit of money. After deploying our software, the client can now dedicate those 8 saved man-days to more important tasks that will drive the development of its business.

Dataddo Use cases

Dataddo 1.2 is public

I am really proud to announce the availability of Dataddo 1.2. We have worked hard to add new functionality, increase overall usability and significantly lower average response time of the application. Amongst significant improvements are:

  • New and simplified GUI.
  • New Facebook Graph API connector.
  • New Google Analytics connector.
  • Updated structure designer with automatic data profiling (suggesting possible connections between sources).
  • Improved data-handling algorithms speeding-up the whole system.
  • New reports.

Dataddo 1.2 is free to use for ANY user with certain limitations (amount of data stored, structures, automated data extractions and reports). If that does not comply with your requirements or you need a custom solution, feel free to contact us.

Dataddo Use cases, Tutorials, Web analytics

Correlation between weather and website performance

This article should demonstrate one of many great features of Dataddo – fusing together data from many different sources and discovering valuable insights for your business. Writing it in the middle of extraordinary long heat wave is giving me an impulse to use long-observed correlation between performance of certain websites and weather as an example.

Methodology

Correlation is “a statistical technique that can show whether and how strongly pairs of variables are related”, therefore it is important to choose suitable datasets representing both variables. In following example I have chosen daily visits reported in Google Analytics in June 2015 to represent website performance and daily temperatures in June 2015 to represent weather. Of course, it is possible to choose other datasets that might fit better to your case such as daily transactions, article views or content interactions for website performance and daily rainfall or humidity for weather.

Obtaining the data

Since Dataddo features many different data connectors, obtaining the data is rather simple. Website performance dataset (daily visits / sessions from Google Analytics) is retrieved using Dataddo Google Analytics connector, setting dimension to “Date” and metric to “Sessions”. Daily temperatures (Prague, Czech Republic) are obtained from Czech Hydrometeorological Institute in CSV file and imported to Dataddo using CSV connector.

Google Analytics connector - daily visits CSV connector

Merging the data

Dataddo allows you to define structure – a collection of one or multiple data sources. Within each structure, you can define 1:1/1:n relations between the sources and thus fuse the data together. In following example date (“ga:date” and Date) is used as “bonding key”.

designer

Calculating correlation

Finally, merged data in the structure can be explored using Data explorer. Moreover, within Data explorer interface many statistical computations, including correlation, can be conducted. The calculated value of Pearson correlation coefficient  for “ga:session” and “AVG temperature” is -0.68, representing a loose negative linear correlation between both variables. As a result, weather (temperature more precisely) has a certain impact on performance of examined website.

explorer

Dataddo Use cases, Strategy, Web analytics

Automated reporting for digital marketing agencies

Internet as a medium changed the marketing communication forever as it brought the ability to measure the activities and therefore more precisely calculate ROI of marketing expenditures. Regardless whether you spend the money on advertising in search, social networks or in on-line display, you have plenty of tools at your disposal to track the effectiveness of each communication channel. As it happens, nothing interesting is ever completely one-sided, therefore employing additional on-line communication channel incrementally increases the need for reporting and thus the workload of internal staff. In a common situation when you use Google AdWords, Facebook Ads and perhaps some other marketing channels at the same time, when a consolidated performance report is required, you need to access multiple reporting interfaces, download the raw data and in some spreadsheet editor manually mash the data together and perhaps to create some graph.

With Dataddo, you can easily mash data from multiple sources together, set automated data synchronization and define consolidated reports. Using Dataddo’s reporting automatization, you can save a considerable amount of workload of your staff. Moreover you can define each consolidated report to be in given time and period automatically delivered via email to multiple recipients.

Dataddo offers a great package of functionality for any industry and user, but its amazing automated reporting functionality is particullarly appreciated by digital marketing agencies. Here is a quick overview of its most important features.

  • Mashing data from multiple sources such as Google Analytics or Facebook Insights together.
  • Automatic data extraction and synchronization.
  • Consolidate reporting and data visualization.
  • Automated report delivery in given time and period to multiple recipients.
  • Branded reports.