Data is bread and butter in modern companies. Relying on your intuition is important but some tools give you an in-depth look. Combining these two methods produces tangible results. Don’t worry, you don’t have to be technically savvy to use data management tools. You just need to prioritize business goals and figure out how they can help you. Here’s a list of the most interesting business intelligence tools you may find useful.

Data management tools

The need for data management tools for FinTech

Before we dive in, let’s talk about the need for having a data analyst on board and for doing analysis in the first place. Even the best big data management tools won’t help if you don’t know what you want to measure and what the reason behind it is.

With the data pulled from your application, you can:

  • see how many users you have,
  • see how many of these users are paying customers,
  • know at what rate all of them use your product, respectively (times in a day, week, month),
  • know their behavior patterns,
  • know what they look for in particular,
  • explore what functionalities are the most popular and how much time users spend on using them,
  • know how much information about themselves users leave in the application and how much you have to guess contextually,
  • design better user experience and user interface (UX / UI design), based on the in-app customer journey,
  • design a clean, understandable and easy to digest in-app onboarding process,
  • recognize and mitigate security issues,
  • assess security and business risks better,
  • optimize pricing policies and plans,
  • create helpful customer support processes and services.

Sounds like a serious commitment to planning, quality execution and overall big workload? Not necessarily. The key is to take it slow, even if you’re not technical.

There are also other reasons:

  • Business intelligence tools help you detect suspicious activities. There are many different compliance laws. U.S. Department of Treasury’s Financial Crimes Enforcement Network (FinCEN), Bank Secrecy Act (BSA), General Data Protection Regulation (GDPR), regulations of Consumer Financial Protection Bureau (CFPB), local anti-money laundering (AML) regulations, and more. In a nutshell – it’s a lot. You don’t want to find yourself on the other side of the law just because something went wrong and you didn’t have enough information. Big money transfers or frequent transfers from multiple accounts to a single account are good examples of suspicious activities.
  • Big Data will assist you in finding new revenue streams. It means not only new functionalities but also increased profit margins from existing ones. It also means finding arguments for creating business partnerships with other companies. Many FinTech products are now partnering up with other companies, even classic banks. What for? Access to technology, client base, promotion budgets. Having more information will let you make the right decision.
  • Data helps deliver personalized marketing campaigns. Including those made within the app. Personalization is at the core of modern FinTech software development. The more you know about the needs, the more accurate your services.
  • Information is key to uncovering market trends. If your users or even paying customers (those are two different categories, after all) start to act in a new and unpredictable way, maybe the wind has changed. In the most favorable situation, they are using functionalities they didn’t have before. In the least wanted scenario, they are leaving because your product doesn’t have what they currently expect from the app. 

Factors to consider before choosing the right product

If something is supposed to work for everything, it’s good for nothing. This old rule turns out to be true in this case as well. You need to think about a few important things before selecting the right software:

  • business reasons behind using business intelligence tools and automated data
  • types of data that your business requires
  • the product’s security measures and ways to safely store data files
  • scalability of the software
  • post-sale support
  • price

Many companies start with the last factor but in our opinion, that’s a risky approach. If you can afford to spend more, do it. Data quality and data integration are worth it. Not to mention the value for your business. If the price is too low, chances are the product won’t be fully satisfactory. And you want it to be – “satisfactory” was used for a reason. It contains a “factory,” which every solid business intelligence and analytics tool really is. A way to produce useable insights based on Big Data. 

The road to business intelligence tools starts with SQL and Excel

If you have a small or medium-sized company, you may want to start small. The best solution for that is… Excel. The old but still immensely powerful tool is great for collecting data and drawing insights. For more complicated use you need data management tools mentioned below but for basics (while developing a minimum viable product, an MVP, for example) it’s more than enough. 

To understand data in your organization, it’s best to learn something more advanced. A good choice would be the Structured Query Language (SQL). You don’t need prior software development experience. You can learn your way around through the series of introductory blog posts, written by an analyst, Hwei-Yi Lee. Unlike many books and courses on the topic, these articles come from the perspective of a business user. They also provide context, necessary to understand more complicated issues.

The power of SQL comes from reducing scary amounts of data to a manageable chunk. It’s done through adding, counting, or averaging numbers that are displayed in repeating categories. That way you don’t have to spend countless hours on data mining. You just need to feed the database and use filters to draw conclusions.

For more advanced users, it’s not enough. That’s where top data management tools come in.

Best business intelligence tools for FinTech

As always in these types of cases – not all of them will be tailored to your individual needs. Not all of them you may find 100% useful for your business. Finally, not all of them will meet your data modeling standards. With all data sources at your disposal, coming from your product and the market, you may want to test them all and find out what suits your business best. There are also factors like the right operating system, options for real-time, data integration and more.

What we provide is a catalog of useful data storage management tools. Which one of them is the best? You just have to find out for yourself.

1.         OpenRefine (previously known as Google Refine). It’s free and open-source software. The powerful advantage is obviously the price, but the list doesn’t end here. The tool is perfect for working with the so-called dirty data. Things like spelling mistakes, punctuation errors, data associated with the incorrect field, or simply incomplete or outdated input are something OpenRefine can handle. It allows work with large data sets, as well as importing and exporting various file formats. You can also upload the data to a central database.

2.         RapidMiner. This software is dedicated to the development of machine learning (ML), data processing and deployments. In reality it is less a single product and more an integrated environment for producing data, machine learning, deep learning, text exploration and predictive analytics.

3.         Power BI. Developed by Microsoft, this powerful product is probably one of the most recognizable among data management tools. Using a well-known ribbon mechanism, Microsoft made the software easy to use and familiar. Accessible to whole teams, Power BI allows self-service business intelligence capabilities. You can create reports and dashboards, compare data and draw conclusions in a safe, familiar Microsoft environment.

4.         QlikView. The product is based on three pillars – data integration, data analytics, data literacy. With them, you can turn raw data into structured data, turn data into actionable insights or build a data-driven culture in your company. The firm has an end-to-end approach that integrates embedded solutions with cloud data management. 

5.         Talend. It’s a unified environment for Big Data, application and API integration, data integrity and governance. It’s particularly useful for FinTech because it has options for masking sensitive personal information. That way you can stay compliant and cooperate with a team at the same time. 

6.         Splunk. It’s one of those big data management tools that are too good to be true. At least according to their website. The company behind it makes software for searching, monitoring and analyzing machine-generated data. It can help by identifying data patterns, providing metrics, diagnosing problems and providing business intelligence.

7.         Xplenty. It’s a cloud-based data integration platform. It helps read, process and prepare data from various databases. It also integrates information from a wide variety of business applications. With it, you can not only dig through data but also manage processes like dataflows planning, task scheduling, and more.

8.         Octoparse. Something else for a change. This type of application can help you with a web-based product. Octoparse is a visual web data extraction programming tool. With a simple point-and-click mechanism, you can extract information directly from your website. You don’t need any coding skills, even basic ones. 

9.         Zoho Analytics. A great in-depth reporting and data analysis software. The product has the function of automatic data syncing; it can be scheduled periodically. An easy-to-use editor lets you create tailored reports. It also has dashboards for highlighting details from important sectors of your business activity. Probably the most interesting feature is a system of comments – you can place a line or two about pretty much everything and share it with the team to improve or talk about later.

10.      Datapine. The product provides an understanding of the complex process of data analytics even for non-technical users. Through the approach of self-service analytics, datapine’s solution enables data analysts and business users alike to easily integrate different data sources and perform data analysis. They can also build interactive business dashboards and generate actionable business insights.

11.      Forest Admin. Forest Admin is an internal tool solution that helps developers save time and provide their business teams with internal tools like comprehensive KYC panels, dashboards, database manipulation tools, and more, that are tailored to their operations and ready to scale. Thanks to its unique hybrid architecture, Forest Admin offers a business-grade level of security.

12. Alteryx. This is a self-service solution. Specialized in data science, it lists finance as one of main industries to serve. Alteryx shines in data mining and predictive analytics. You can upload data from multiple sources (like Salesforce, for example). After analysis, the platform can generate the report and convert it to the desirable format.

13. KNIME. This is an open-source solution. One of the immediate bonuses you will see after launch is simple and intuitive, yet very powerful UX with multiple options available at your fingertips. It’s not obvious for free software, so kudos are in place. You can pull data from various sources, such as Azure or Google Sheets and KNIME will sort and filter it. Then it will prepare data for machine learning processing, and create machine learning models. With explanations to the user. Then you can export the results into various formats.

14. H2O. The platform is heavily AI-based and offers specialized modules for FinTech. Services like credit risk scoring, freud detection, anomaly detection, customer churn prediction or Know Your Customer (KYC) will help businesses extract value from their data.

15. Board. Board is a Business Intelligence and Corporate Performance Management solution used in the banking and Fintech. It allows you to test different scenarios through automatically updated live dashboards displaying real-time data. It’s time-efficient, since you don’t have to create a new model for every scenario. You can extract data from CRM, cloud, ERP systems, flat files, etc.

What does the architecture of the best business intelligence products should look like?

There is no such thing as perfect software. That’s why software companies have clear roles in the development process. The other thing is that the client should be involved as well. The third part is the role of the post-launch process when additional services and maintenance can do the trick for further business development. The one problem with it is that none of that will work if we don’t think about the right architecture.

Because we are dealing with information, the good data management tools you will shop for should have the characteristics mentioned below. The data can’t be scrambled, the access to it should be seamless, and ways to draw conclusions should be transparent. But in more detail:

  • the application should have modules for analyzing different kinds of data: about the product, its usage, paying customers, users of a free trial, sales, etc.
  • the source data should be gathered and referenced to give you the output data as a result
  • the product should have the ability to hide or block access to sensitive information (like customer’s name, address, income, etc.)
  • the product should have data quality, operations, and Service Level Agreements (SLAs) standards
  • there should be an option to apply security policies to each individual data entity

In a perfect world, all products would have a complete list of these features. Many of them do. The real trick is to balance your business needs, budget and what companies have to offer in return.

Mess with the best, die like the rest

This catchphrase is highly esteemed by players of video games because it was a part of a very popular commercial around 20 years ago. As it happens, it works great for data and business software. Without the data, you’re crippled and can’t perform at full capacity. Without quality software services, it will be hard to build a performing application.

The best big data management tools are the ones that can put you on the way to higher profits. There are lots of products to choose from but one question remains – what are your business goals? This is the one you can’t miss, everything else branches out from here.

You need partners that understand where you’re coming from and what the destination is. There are many FinTech software services, for different needs. Choose those which are tailored to your specific roadmap.