Introducing the basics of data visualization and its use in the finance industry

Data visualization is a powerful tool that has gained immense popularity in various industries in recent years. The finance industry, in particular, has been leveraging data visualization to gain valuable insights and make informed decisions. Put simply, data visualization is the representation of complex data in a visual format that is easy to understand, making it an efficient method of presenting data and uncovering patterns and trends that would otherwise be difficult to identify. By using graphs, charts, and other visual aids, finance professionals can quickly analyze data that could take hours or even days to go through manually. With data visualization, they can easily visualize changes in stock prices, track market trends, and make informed investment decisions based on reliable data. The finance industry has already witnessed a surge in the adoption of data visualization, and it’s only going to become more critical in the coming years.

How data visualization helps to identify patterns and trends in financial data 

Financial data is incredibly complex, and it can be challenging to find patterns or trends within it. This is where data visualization comes in. By presenting financial data in a graphical form, it becomes easier to identify patterns or trends that might not be readily apparent when looking at spreadsheets filled with numbers. Graphs and charts allow us to see relationships between different data points and track changes over time, helping us make smarter decisions about our money. In addition, data visualization can help highlight outliers or discrepancies, alerting us to potential issues that could impact our financial well-being. By embracing data visualization, we can gain insights into our financial situation that might otherwise remain hidden, empowering us to make informed decisions about our money and investments.

The importance of understanding data correlations in order to make better decisions

In today’s data-driven world, the abundance of information can be both a blessing and a curse. While numbers and statistics can provide valuable insights, interpreting them correctly is key to success. That’s where understanding data correlations comes into play. By analyzing the relationships between different variables, decision-makers can identify patterns and trends that would have otherwise gone unnoticed. From marketing to finance, data correlations can inform a wide range of decisions, from staffing to product development. In short, mastering the art of data correlations is essential for anyone who wants to make informed, effective decisions.

Examples of common visualizations used to display financial data, such as line graphs, pie charts, and more

Visualizations are essential in displaying financial data as they help people make sense of complex information. When it comes to financial data, line graphs are one of the most commonly used visualizations. They are perfect for showing how a particular metric has changed over time. Pie charts, on the other hand, are great for displaying how portions of a whole are distributed. In situations where data needs to be compared, bar charts are perfect. Heat maps are also excellent options for displaying financial data, mainly when data is spread across different categories. These are just a few examples of the types of visualizations that are commonly used to display financial data. Each offers unique benefits and can be used to tell a compelling story about the data presented.

Tips for using data visualization to gain insights into the financial markets 

In today’s data-driven world, using data visualization to gain insights into the financial markets is more important than ever. Data visualization allows us to present complex financial information in a simple, visual format, enabling us to identify trends and patterns that may otherwise go unnoticed. When it comes to financial markets, data visualization can help provide a clearer picture of market trends and movements, allowing us to make informed decisions about investment strategies. With the right tools and techniques, data visualization can be a powerful tool for understanding the financial markets – and staying ahead of the competition. Whether you’re a seasoned investor or just starting out, incorporating data visualization into your financial analysis toolkit is certainly worth considering.

Benefits of using data visualization for investors and analysts alike

Data is a powerful tool that can help investors and analysts make informed decisions. However, raw data can be overwhelming and difficult to comprehend. That’s where data visualization comes in. By presenting data in a visual format, investors and analysts can quickly identify trends and patterns that may have been missed in raw data. Visualization makes it easier for them to see the big picture and make data-driven decisions. For example, by seeing stock prices visualized over time, investors can quickly identify trends and make predictions about future prices. By using data visualization, investors and analysts alike can save time and make more accurate decisions.

Conclusion

Data visualization is a powerful tool for analyzing financial data and gaining insights into the financial markets. By using visualizations to identify patterns and trends, investors and analysts can make better decisions based on the correlations among various data points. Visualization is not only useful for those who are knowledgeable in finance but also for novices to the field who want to gain a foundational understanding of their investments. Through the use of line graphs, bar graphs, pie charts, and other visuals, one can more clearly evaluate their strategies as well as compare different strategies with that of their peers. Whether you’re an amateur or a veteran investor, be sure to take advantage of data visualization techniques in order to get the most out of your financial portfolio.

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Qlik Sense is an application for self-guided data visualization, research, and monitoring. The user-friendly, intuitive interface requires no special knowledge of data processing and is recommended for all company employees. User screens can be customized by simply “dragging and dropping” items onto the work screen. The ability to process data directly in RAM allows you to operate with large volumes of information.

Advantages of Qlik Sense:

• Easy implementation, support and scalability
• Open standard APIs for developing your own applications
• Ability to embed Qlik Sense into web pages and own applications
• Easy integration with various data sources
• High speed of work with large data volumes
• Support of different devices – from PC to smartphone and touch-screen tablet
• Compliance with enterprise security policies
• Individual and group work with data
• Built-in data library that’s replenishable and available to all users
• Ability to collaborate on data both within the company and with customers, suppliers and contractors thanks to Qlik Sense Desktop, a free Windows application
• Intuitive interface – even for users without special knowledge
• No need to involve IT specialists for editing
• Quickly create your own interactive dashboards, dashboards and reports or use the preconfigured ones.

Qlik Sense uses all the advantages of technology and experience of Qlik, the world’s largest developer of business intelligence systems. At the heart of Qlik Sense is a combination of intelligent visualization and search capabilities with Qlik’s patented associative data indexing mechanism. No scripting is required to work with Qlik Sense, and the data needed for analysis can simply be dragged and dropped.

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Lately, interactive infographics have become an increasingly popular tool for journalistic content creation. One of the key products for collecting, sharing and visualizing large amounts of data has been a tool like Google Fusion Tables, launched in June 2009. It’s a Web-based application that can create charts, tables, graphs, layouts and maps in minutes.

Fusion Tables stores information in the form of multiple tables that can be viewed and downloaded by Internet users. The essence of the service is to share, collect and visualize these tables. The functionality provides the ability to build pie charts, scatter charts, histograms, line graphs, time charts, and (the most common application) geographic maps. Data is exported in CSV format.

Structure of Fusion Tables

Queries to the service come from several possible sources:

• Fusion Tables website;
• standalone applications that use the API;
• visualizations embedded in other web pages (e.g., diagrams).

Next, query-based map layers are generated, which can be spatial or structured. The foreground database manager converts the queries into a generalized representation and passes them to a specialized processing module, which then creates a query project. The project is executed with the help of a structured back-end database using a set of synchronously replicated Bigtable servers. The main task of Replicated Storage is to process hundreds of thousands of tables with different schemas, sizes and characteristics of the queries being loaded.

Storage Stack

Fusion tables are built on a two-tiered storage stack in Google.

Bigtable: the tuples stored there are key-value pairs, sorted by key and distributed across multiple servers based on their ranges. Part of a tuple value can be a complex value of some normal form (except the first one). Bigtable provides a write operation that atomically inserts a new tuple. The service also provides three read operations:

• Key search, which retrieves a single pair with a given key;
• key prefix search, which retrieves all pairs with a given key prefix;
• key range search, which retrieves all strings between the start key and the end key.

In addition, Bigtable records the transaction history for each tuple. That is, internally a tuple is stored as a “key, value, timestamp” triplet, where the timestamp captures when the tuple was written. In general, one key value is used in multiple versions of tuples.

Megastore is a library above Bigtable. It provides higher-level primitives such as sequential secondary indexes, multiple row transactions, and sequential replication. The specified library is used:

• To support property indexes,
• for providing table-level transactions,
• for replicating tables across multiple datacenters.

Fusion Tables API

An important aspect of creating a data management and collaboration platform is to allow developers to extend the functionality of the platform. This is accomplished through the use of an API. It allows developers to create applications that use FT as a database. For example, the website mtbguru.com, which hosts a collection of bike routes, wrote an application that synchronizes them with Fusion Tables. The API supports querying, modifying, and defining the data using the appropriate operators and instructions. At present, modifying Fusion Tables schemas through the API is not supported, and existing standards are used for authentication and data access.

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Solver is a corporate performance management suite that enables faster and better decisions using a single, cloud-based solution that automates reporting and planning processes. This CPM tool includes powerful features and seamless out-of-the-box integration with many business management solutions like SAP Business One and Microsoft Dynamics 365.

Solver comes with capabilities and functionalities that allow the analysis of data from multiple data sources that are stored in a data warehouse that allows users visualise trends, generate reports in any format you require and also to dive down to the smallest details. Organisations utilising Solver have the ability to create effective business plans, schedules and execute budgets and drive growth to optimum levels.

Solver is a popular Corporate Performance Management (CPM) tool which automates the collection and analysis of data. Its drag and drop functionality, versatility and highly adaptable budgeting model allows the creation of accurate forecast and reliable models.

Additionally the data warehouse module comes equipped with out of the box intelligence around financial reporting capabilities, enabling them to combine all their data and base their decisions on reliable information and actionable business insights.

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Gephi is an open-source software package for visualizing and analyzing linked data. This package is written in Java for the NetBeans platform, so a Java Runtime Environment (package jre) version 7 or higher installed on the user’s computer is required for it to work correctly.

You can say that Gephi is in some ways similar to the tools used for process-mining and familiar to everyone Excel. That’s why its mastering shouldn’t be too difficult for an analyst.

The key features of this package are as follows:

The package supports a wide range of input data presentation formats, such as GraphViz, GDF, GEXF, GML, GraphML formats, and most importantly, the source file for this system is similar in structure and extension to the CSV file familiar to analysts involved in PM data analysis.
The package has an open license, which means it can be freely used not only by analysts, but by programmers as well (the source codes are available on the website of the software package), which contributes to fast development of the package and appearance of additional modules to solve various tasks (the latest version of Gephi with source code is located in the repository at Release Gephi 0.9.2 – gephi/gephi – GitHub).
The package provides a wide range of settings for adjusting the graph display. It allows the end user to adjust graph rendering independently during analysis – the main slogan of Gephi is “Gephi makes graph handy” – Gephi completely tames graphs.

This tool is more complicated, requires some learning, source data is a bit more detailed than usual logging for process-mining. It means that graph analytics will require more preparatory work on the source data, namely two files must be prepared for uploading to Gephi:

A vertex file (the vertices of the graph are objects), which must necessarily have an ID field. This file is enough to construct an undirected graph.
The file of edges (edges are links), which must contain the fields of Source (Source, the starting point) and Target (Target, the point where the flow of information in the graph is directed).

Loading source data takes place in several stages. At each step, Gephi checks that the data is correct. You can filter data loaded in Gephi in a way similar to MS Excel, and you can filter the number of nodes and edges of a graph using regular expressions and logical operators. You can also set size and color for graph nodes/edges and labels either by specifying a variable value when you load the data or by generating it in Gephi’s settings.

If you want to learn graph methods of data analysis from scratch and master a new graph visualization tool, Gephi is ideal for you – open, constantly refined and enriched with new tools to solve modern problems of applied modeling and data analysis using results and the latest advances of modern network science (Network Science).

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Tableau Public is free BI software that lets you connect to a spreadsheet or file and create interactive data visualizations.

Tableau Public is one of the company’s products designed for novice site analysts, bloggers, journalists, and students. The main difference between the program and Tableau Desktop or Tableau Server is that all reports and data uploaded to Tableau Public, become public. But this does not deprive the program of all the advantages of its commercial brothers. It seems that you can not use Tableau Public commercial organizations? No. You can and you should.

Tableau Public – a presentation tool

Tableau Public only from the outside seems to be an introductory product, designed only for novice analysts or students. In fact, many companies around the world use Tableau Public for commercial purposes. The most obvious example is presentations.

Let’s suppose that future business partners regularly ask your company to provide additional information about itself, about the number of executed orders, conducted researches, speed of contracts execution. Usually commercial departments make PDF presentations, sometimes these files are published on companies’ sites, but more often they are sent by e-mail upon request. However, much more impressive would be an interactive report uploaded directly to the company’s site.

Tableau Public is a free product – you can and should use it. If you are just thinking about buying a commercial license for Tableau Online, you should start your acquaintance with the program from Tableau Public. The program is ideal for the first introduction to the Tableau family of products.

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Infogr.am is one of the most famous services for creating infographics, which has become popular due to its ease of use and rich functionality available already on a free account.

Let’s analyze step by step and carefully what features this resource provides. It’s worth noting that its interface is not translated into Russian, but many of the available functions are presented in the form of clear pictogram buttons, speaking for themselves.

First of all, we need to register on the site, or enter through an account in social networks. After that, the service offers us to get down to business immediately – to start with design or to load data for its creation (start with data). First of all let’s consider the first option.
So, we click on Infographic or report, and then you can choose the design for the project. The difference between the first and second buttons on the left – Infographic or Report and Chart of Graph – is that in the second case, you only create the graph itself, without any additional explanations, design settings and so on. So let’s look at the first, more complicated way, although in general it shouldn’t be difficult to work with Infogr.am.

Some of the options described here are available in the basic free account, and some are only available in the Pro version. Please note that these are color combinations only, and you can change the look and type of the graphic itself later during the work. By default, your project will be available to everyone on the network, and private access is also a paid option. Then enter the name of your project and click Create.

Once you’re done creating infographics, you need to put them on your site page. You can’t just download it – as a pdf or as an image – on a free account. To do that, click on the Share button in the upper right corner and choose how exactly we can share our creation – via a link on social networks, via email, or still as an embeddable object on a web page. There are separate settings for the latter option – such as adaptive sizing, which is important to accommodate audiences with mobile devices, and special code for WordPress sites.

If you go from the data?

As we noted at the beginning, you can start creating infographics not with the design settings, but with uploading data – in case you have it stored as text documents, tables or in other structured form. To do this, you’ll need the Add Data button in the main left-hand menu. Then it is assumed that the site will automatically recognize the entered information, and you will only have to adjust the appearance of your infographics as described above.

So, working with Infogr.am is quite simple and intuitive. Now try it for yourself

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