The Silicon Review
by Angie Piparo, General Manager, Javlin Inc.
It’s no secret that data assets are increasing exponentially. With this dramatic growth in volume and complexity, the need
to move, manipulate, and analyze data is taking center stage. Today’s imperative is to design a data workflow optimized for
performance, agility, and usability. CloverETL’s data integration software suite meets that challenge with compelling data design.
Why focus on data design as a foundation for great software? Because you can’t just write the best code; you have to extend the use of the software more broadly into user-driven experiences for customers, executives, business analysts, and data scientists across the board. Well-designed data architectures must be naturally inclusive, and can actually unify constituents for business goals.
Data workflows are shifting continuously with new sources and targets, and software developers must adjust by employing smart data design. Data is regarded as the new oil and the data infrastructure pipelines must be flexible enough to change direction as quickly as the business demands. With this in mind, leaders must be planning on future proofing their most
valuable asset – data.
There’s a reason the CloverETL software exemplifies agility and good design; it started with a vision of doing something better from a real life software developer.
CloverETL founder David Pavlis began with a goal to write a Java-based software that replaced classic C++ code-driven ETL tools. The Java approach provided both a lightweight footprint and the flexibility to run on many different platforms enabling independence. The deeper vision was to help customers solve their data problems in a straightforward way without a steep learning curve. His predicate to craft an excellent software with inherent design and solid code represents a hallmark
of CloverETL then and today.
What’s evolved is a powerful and reliable data integration workhorse that can be used to populate a data warehouse, feed applications, or enable analytics strategies. Users can orchestrate their entire data workflow around complex business rules while also monitoring and notifying a team about key issues. What’s interesting is that both large and small enterprises depend on CloverETL to do heavy lifting for their precious data. One customer recently put it well: “Whatever I can envision, I believe I can do in Clover. I don’t feel limited.”
Data Design Gets Personal
Before joining the Clover team, I spent years as a technical consultant doing data migrations the hard way, through scripting. As I started working with CloverETL I found my experience more intuitive, which made it easier to design complex workflows. I was able to look at frameworks built by my technical colleagues and quickly add or modify functionality as our customers’ business rules changed. There was no more digging through thousands of lines of inherited code to tweak
a data workflow and no more frustration of writing code for similar tasks, over and over again.
As I became more proficient in data design with CloverETL, I saw the art in building a flexible framework that could handle changes in data sources, targets, and governance. It became clear that proper design saves valuable development time. Moreover, the business value of CloverETL extends beyond just good data design; the tool actually frees consultants and developers to work on greater application-driven strategies.
With great design also comes ease of use. What I saw when training users on CloverETL, from large enterprise to startups, made me a believer. Even though they varied in skill sets, from heavy Excel business users to sophisticated Java developers, everyone was able to quickly take CloverETL and build a solution. The investment in pipeline design also enabled better data insights because clients were now working with a reliable, flexible data approach. It was easy to tweak as they started to
understand their data.
The Future For Data Design
The data industry is now moving beyond a singular concept of “big data” due to the global enormity of data systems. Forrester says worldwide big data solutions are expected to grow at a compound annual growth rate (CAGR) of 12.8% from 2016 to 2021. Further, the Cisco Global Cloud Index projects 10.4 zettabytes (ZB) in global data center IP traffic by the end of 2019, up from 3.4 ZB in 2014. The realization that one zettabyte equals one trillion gigabytes seems to make the task of managing data unfathomable – but we don’t see it that way.
It’s been said that very large companies hold the edge in the future of data management and integration because they have
access to so much of the data. However, storing or massing large data sets, records, and files does not necessarily guarantee a well-designed system. What’s needed is a focus on the value of the data source as it relates to the application and CloverETL’s
designed workflow encompasses this. Data design is something required more than ever before.
In addition, future emphasis on performance without a ton of overhead is also needed. Small enterprises can’t just hire a small army of IT consultants to manage their data; they also must be able to rapidly ingest, validate, analyze, and move data to be self-sufficient in their workflows. The power of CloverETL represents their independence and the future in data design.
CloverETL Commitment To Sharing Know-How
Talking about data design and how powerful the CloverETL data integration software is one thing, but sharing understanding about how to use good design with trusted know-how takes it a step further.
We encourage data developers, consultants, and business leaders to check out CloverETL
Angie Piparo is the General Manager of Javlin Inc., a subsidiary of Javlin Group which owns and manages the CloverETL
data integration platform. She can be reached at firstname.lastname@example.org