Dirty data problem is caused by a process problem
In the last two years, over 90% of the world’s managed data was created. According to IDC, there were 2.5 quintillion bytes of newly generated data daily in 2015 and that figure is projected to accelerate at an annual rate of 30%. In some respects, this can create more problems to deal with, but it also means that there are more opportunities for businesses like yours considering they have the right software which allows them to utilize intelligent insights in their day-to-day operations.
Growth in data is great as it helps businesses to flourish, but companies need to be sure they have a well-established data infrastructure in place to deal with vast amounts of information. Some challenges that should be considered are:
- Collecting, storing, sharing and securing data.
- Creating and utilising meaningful insights from their data.
It’s not easy, but there are pragmatic solutions to overcome data storage problems. For example, a good recommendation would be to plan ahead and have dedicated teams who will do the data clean-up job for you, allowing you to focus on bigger and more important parts of your project.
Table of Contents
- What do common financial data management problems look like?
- How to handle large amounts of data exponentially growing on an annual basis?
- How to unify data across dozens of disparate systems?
- How to get rid of a mainframe system that no one born within the past 50 years knows how to maintain?
- How to structure unstructured data?
- How to avoid data-entry mistakes?
- How to leverage data to make an impact your customers will actually care about?
What do common financial data management problems look like?
People who work with numbers in the business world on a daily basis find it easier to manage their tasks effectively. Financial data management is a tricky part that can make or break a company. Businesses can easily lose a lot of money by mismanaging their financial data. It takes a lot of organization to make sure that financial data is kept safely and securely. People who are committed to the future of their company will strive to stay on top of their financial data management.
- Exponential growth: Finding ways to store and keep track of your data is a common challenge among software companies today. Human- and machine-generated data is increasing more rapidly than traditional business data. Specifically, machine data is estimated to grow 50x faster than human-generated business data over the next 5 years.
- Storage: Big data challenges for banks start with the way information is stored — up to dozens of disparate systems across a typical bank.
- Outdated infrastructure: Legacy and mainframe systems have proven extremely difficult to shed in some instances.
- Data synchronization: Banking data can be so hard to keep up with. Some data may disappear while introducing mistakes, while there are still others that just seem to be missing from where they should be because of various reasons.
- Unstructured information: ID cards, birth certificates, articles of incorporation, contracts and emails are all unstructured data.
- Mistakes: Data management challenges are also exacerbated by simple mistakes that anybody could make.
How to handle large amounts of data exponentially growing on an annual basis?
Data ingested is not automatically sorted and classified by a computer. The somewhat tedious manual process of sorting and classifying this data is time-consuming and takes up valuable time. Using machine learning, there are algorithms that can be created to parse through the data, classify it, and sort it in a manner that can be quickly used by a computer program.
How to unify data across dozens of disparate systems?
The easiest way to automatically copy customer data from one environment to another is to set up an API-based copy program that takes advantage of cloud-based APIs. The APIs can either be SaaS or on-premises-based depending on what you’re trying to move. This is best for repeated, ongoing data migrations. You can also use a robotic process automation (RPA) platform to streamline the process of data migration between platforms. At the end of the day, you want to make sure your customer data is being transferred securely and efficiently, which is why data migration is so much more than just moving it from one place to another.
How to get rid of a mainframe system that no one born within the past 50 years knows how to maintain?
Not only is automation a way to replace human labor, but by automating solutions, you’re also able to remove the inefficiencies of traditional solutions. For example, if you automate the process of storing files, you could access them so much faster than you could with a physical solution.
How to structure unstructured data?
You can integrate information extraction models into a data operating model in order to act on the data you’ve extracted. Information extraction models go through data and pull out important information. This can be anything from the location and price of a property, to the key ideas of a book. Information extraction models are particularly useful when investigating a large amount of data where you’re looking for specific data points. Since you can extract only certain data points, it’s a lot more efficient than manually going through the data and identifying the key points.
How to avoid data-entry mistakes?
If you automate a process, you can reduce the workload on your employees, so they can focus on more important things. It also helps you reduce the amount of money you spend on employees, thereby increasing profit. The best way to reduce dependency on people is to have the computer do most of the work. You can either buy a piece of software or write one yourself, or hire someone to create a software program for you that will automate a process. If it is software, it’s important to make sure it is of high quality, because bad software can cause a lot of problems and lose you money, as opposed to saving you time and money.
How to leverage data to make an impact your customers will actually care about?
Simplify your business processes by creating a data layer and streamlining the workflow in your organization. Have access to a data engine for data-warehousing, intelligent data routing and mapping tools, single sign-on tools, data security tools, and an integrated platform of user-friendly tools, integration components and connectors, and APIs.
In today’s data-driven world, the management of your data is essential and must not be ignored. You need to be proactive in understanding and implementing data solutions that align with your business goals. By doing so, you can effectively mitigate any big data problems before they even arise. Some organizations have the advantage of being able to invest more time and money into building out a team of data scientists. But even if they don’t, there are some data tools that allow business leaders to leverage the skills of their staff in turning data into insights.If you need to automate your business, but you don’t have development skills, using a platform like Integromat is the perfect solution. Integromat doesn’t require a single line of code and has a large library of over 17 pre-built integrations for popular business applications, including WordPress, Shopify, and Facebook. You can also use Integromat to create and schedule popups, landing pages, and surveys to collect user data. Also, we suggest the Integromasters course for you to learn automation and adapt it to your business processes, and for a limited time, the demo is free. Act fast before this special deal ends! You can pay with credit card, bank transfer or bitcoin. You can learn more by joining their Facebook group or by visiting their website.