data strategy

How to win the battle with data fragmentation

Posted on by Zdenek Pecha

How can I move my data management methods into the 21st century?

Let me tell you a story which that unfolds every day in thousands of offices around the world. Imagine a guy, let’s call him Joe. Joe is sitting behind his desk, looking at the monitors he rummages through dozens of reports from the various web services that his company utilizes.

On the one hand he is using Google Analytics and Adobe Analytics to track his website, Facebook, Instagram, LinkedIn and YouTube to share content and build a community, Smartly to manage social advertising, Google Ad Manager and Google Ads to run the campaigns,  Stripe for billing and Salesforce as a cloud CRM,  Brandwatch to get insights about his brand, Social Bakers for social media management and monitoring. Some of these tools are used for internal purposes and some on behalf of his clients.

And on the other hand, Joe is using Tableau, Google Data Studio, Klipfolio, Zoho Analytics or other tools to visualize this data. Now Joe is asking a simple question. How the hell do I consolidate and make sense of all of this data? How can I handle it all without a team of developers to consolidate all my company’s data infrastructure?

Joe is stuck, he is desperate and he is out of time because he needs his consolidated reports now, he needs them quickly and he’ll need them again tomorrow and likely next week. Moreover, his needs may change in a few weeks and he’ll need to reconfigure his data infrastructure quickly.  

So what is the solution for Joe? The answer is a flexible and universal no-code data integration platform capable of connecting all of his data sources and consolidating the data, prepping it and delivering it anywhere anytime he needs. He needs to be able to connect his sources to any BI tool, data warehouse or FTP/FSTP server and it needs to be easy to execute.  Why? Because it’s 2019.  The days of manual data handling processes are over. This solution has only seven letters – Dataddo.

Does this story sound familiar to you? Give Dataddo a try and solve all of your data problems in just a few clicks. Dataddo connects all of your data sources to your BI tools, dashboarding apps and data storage solutions because sometimes being retro is cool, but not when it comes to working with your company’s data!

0
data strategy

Making Klipfolio a Fitting Piece of Your Existing IT Puzzle

Posted on by Zdenek Pecha

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.

0
data strategy

Zoho Analytics + Dataddo – A Complete Data Analytics Package

Posted on by Joel Thom

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!

0
Dataddo tutorials

Basic components of Dataddo

Posted on by Zdenek Pecha

Our society and businesses are increasingly more depending on data. As new and new services and storages are coming to the stage and as well as they are being adopted into the business environment is increasingly difficult for businesses to work with those data and storages. If you want to be effective you have to find a way how to handle it, you need a service or a tool which accommodate all those data sources and which is flexible enough to be easily interoperable to your existing IT stack. And this is a time when Dataddo is coming to the stage.

Dataddo is a data integration platform that helps organizations easily compile data from any online source and efficiently bring it to the various business intelligence tools, dashboarding apps or existing data warehousing ecosystems.

Data sources

Dataddo is composed of three basic components. A section called Data sources gives you a list of available native connectors to various online services. We are talking with services like Google Analytics, Facebook Insights, Twitter Ads, Instagram, and many others.

Data destinations

In the business intelligence and dashboarding apps section, you can choose from a various list of outputs where you can push your data. We have connectors to various storages systems such as Google Big Query, AWS Redshift or even your own on-prem deployed SQL-based databases. You can also easily connect services such a Tableau or Google Data studio.

Integration flows

The central part „The Integration flows“ orchestrate all the integrations. Here you can easily manage the extractions from your various data sources and automate the final delivery of your data to your dashboarding applications or storage solutions.

0
data strategy

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

Posted on by Petr Nemeth

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.

0
data strategy

Data fabric identified by Gartner as one of the key data and analytics trends

Posted on by Petr Nemeth
Artistic visual of data fabric

The idea for building the Dataddo platform came from the knowledge that many data experts find it extremely painful to work with analytics data from multiple web, social, sales and customer platforms. Having this insight, we identified a need for a no-code data integration platform that helps businesses centralize all of their analytics data into a single place whether that’s a dashboarding app like Tableau or Google Data Studio, their data-warehouse or a cloud-based big data storage. We are excited to see that our initial vision for building Dataddo has been validated by the world’s most respected IT research and analytics firm, Gartner.

Gartner listed data fabric as a key data and analytics technology trend. 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.”

0