Exploring a modern solution to take on the heavy lifting of data management
Nowadays, data is a hot commodity with extremely high value. However, the real value of that data comes down to its management. You see, the data itself has little to no value until it has been sorted, cleaned, and analyzed. Without that process, the data piles up quickly, uselessly collecting theoretical dust.
To be frank, this is a painstaking process that very few individuals have the expertise to handle. Furthermore, for those that do have the technical understanding, it is tedious and clumsy. There must be a solution.
The pains of data digitization
For businesses, digital transformation brings many incredible benefits, such as improved efficiency, revenue growth, and increased customer satisfaction. However, the complicated process of digitalization is not for the faint of heart, in particular for the data analytics and infrastructure space.
Firstly, a huge quantity of the world’s data is trapped offline in CSV and Excel files that are stored locally or emailed. Secondly, offline files do not work well with software applications, analytics, or data science needs. Moving data to production databases is also very difficult and requires high technical skills. As a result, it is common to see fragmentation, inconsistency, and mismatched data models. And, not surprisingly, data hand-off is often incompatible between technical and non-technical teams.
In particular, for businesses that are well established, making the shift from offline to online systems is highly time-consuming. Years – or even decades – of documents must be captured, which is labor-intensive and, therefore, costly. Furthermore, many companies do not have employees with these unique technical skills.
Data overwhelm
Even when a business successfully captures its offline data, the struggle is not over. For many, the sheer quantity of data becomes problematic. Basic tools, like Excel, simply reach a limit becoming bogged down and slow. For most, the initial data models used within the company are no longer efficient or relevant as the business grows.
According to Tech Jury, 80-90% of the data we generate today is unstructured, with 95% of businesses citing the need to manage unstructured data as a problem for their business. This is where data management becomes absolutely critical. It is essential to hire talent that has a deep technical understanding of data analytics and integration, and it is also imperative to find systems that can successfully support this transition.
How to make sense of it all
In order to succeed, the data of a business must be digitized in the most beneficial way for the company, in terms of actually utilizing that data. There are a variety of online data management platforms available like Sheety, Sheetsu, and Dropbase.
Sheety, for example, enables customers to instantly convert any Google sheet into an API for free. All you need is a spreadsheet to create powerful websites, apps, or whatever else you want. Your API is updated in real-time when you make changes to your spreadsheet, saving you precious time. Similarly, Tomek Popow, the founder of Sheetsu, created the tool to allow users to connect Google Sheets to Web, Mobile, IoT, or any service's API.
When considering the common struggles of data management, Dropbase co-founders Ayazhan Zhakhan and Jimmy E. Chan saw many issues. They found that customers are under-utilizing their data that was “trapped” in offline files or in software systems that could not integrate with other tools, and non-technical teams are paralyzed due to the lack of technical resources available to solve data problems. They also noticed the single point of failure, resulting from improper tools and processes used to maintain large master datasets collaboratively.
Dropbase empowers individuals, teams, and businesses to streamline and automate repetitive data cleaning workflows. The platform makes it easy for spreadsheet users to collect, clean, and centralize data from external sources seamlessly. External data can come from offline sources such as CSVs and Excel files, or online sources such as Shopify, Salesforce, and Hubspot. As with other data management platforms, Dropbase users do not need advanced technical knowledge to set up data infrastructure or build scalable data pipelines.
Final thought
In order to successfully handle the complexities and demands of the digital age, we need digital-ready data management solutions that update and streamline procedures. Whilst there is useful information in data, it ultimately depends on how it is managed. By utilizing tools such as Dropbase or Sheety you can easily streamline the process of digitizing your offline information to better manage and access your data.
