The Best Data Analytics Software for Auditors can help you make deep insights, as well as it helps to reveal the hidden insights from your data. The best analytics auditors should choose Best Data Analytics Tool for Auditing. This software is a powerful tool that can support you to perform analytics audit for complicated systems.
Discover the best data analytics software for auditors with this independent review of five top business intelligence tools. Each product is scored on their ability to cope with large data sets, create attractive charts and graphs, provide powerful analytical tools, operate in the cloud, offer an excellent range of pricing packages, give access to open source software.
TIBCO
TIBCO is a Data Analytics software platform that uses ‘Machine Learning Augmented Data Analytics’ and is suitable for either proficient Business Analysts or freshers. Gaining real insight from streaming analytics is TIBCO’s key feature, which enables it to offer data mining on the run, with the knowledge of trends in data accumulated from the torrents of data streamed from the Internet of Things (IoT) or other devices.
SAS
SAS is a complete analytics software that is suitable for a large organization’s data mining process. Its Data Analytics tools and techniques use ML, AI, and automation to meet Business Analytics requirements that allow all aspects of next-generation data mining, from prep to visualization.
Xplenty
Xplenty is a cloud-based Data Analytics software that unifies all of your data sources. It offers Data Analytics tools and techniques to keep your marketing automation up-to-date.
SAP
SAP has a strong functionality with augmented Data Analytics tools and techniques, making it one of the best Data Analytics tools. It has a fully integrated Data Analytics tools list that offers complete analytics functionality in just one analytics software. Its cloud-native multi-cloud compatibility feature allows a menu of API to connect with embedded solutions.
Hitachi Vantara
Platform: Pentaho Platform
Related products: Lumada Data Services, Pentaho Data Integration
Description: Hitachi’s Pentaho analytics platform allows organizations to access and blend all types and sizes of data. The product offers a range of capabilities for big data integration and data preparation. The Pentaho platform is purpose-built for embedding into and integrating with applications, portals, and processes. Organizations can embed a range of analytics, including visualizations, reports, ad hoc analysis, and tailored dashboards. It also extends to third-party charts, graphs and visualizations via an open API for a wider selection of embeddable analytics.
ibi
Platform: WebFOCUS
Related products: WebFOCUS Designer, Omni-Gen data management
Description: The WebFOCUS platform features self-service analytics and data discovery, a visual discovery insight mode, predictive capabilities, and more. WebFOCUS can deploy secure applications to millions of users, and governance enables metadata-driven delivery across an organization. The platform also extends beyond dashboards for executives and analysts by operationalizing data and analytics for line-of-business users. Information Builders offers a complete portfolio of big data tools, from integration all the way to advanced analytics and data management.
IBM
Platform: Cognos Analytics
Related products: IBM Watson Analytics, IBM Watson Studio, IBM Hybrid Data Management
Description: IBM offers an expansive range of BI and analytic capabilities under two distinct product lines. The Cognos Analytics platform is an integrated self-service solution that allows users to access data to create dashboards and reports. IBM Watson Analytics offers a machine learning-enabled user experience that includes automated pattern detection, support for natural language query and generation, and embedded advanced analytics capabilities. IBM’s BI software can be deployed both on-prem or as a hosted solution via the IBM Cloud.
SQL CONSOLES
SQL is programming language that is used to manage/query data held in relational databases, particularly effective in handling structured data as a database tool for analysts. It’s highly popular in the data science community and one of the analyst tools used in various business cases and data scenarios. The reason is simple: as most of the data is stored in relational databases and you need to access and unlock its value, SQL is a highly critical component of succeeding in business, and by learning it, analysts can offer a competitive advantage to their skillset. There are different relational (SQL based) database management systems such as MySQL, PostgreSQL, MS SQL, and Oracle, for example, and by learning these data analysts’ tools would prove to be extremely beneficial to any serious analyst. Here we will focus on MySQL Workbench as the most popular one.
MYSQL WORKBENCH
KEY FEATURES:
A unified visual tool for data modeling, SQL development, administration, backup, etc.
Instant access to database schema and objects via the Object Browser
SQL Editor that offers color syntax highlighting, reuse of SQL snippets, and execution history
MySQL Workbench is used by analysts to visually design, model and manage databases, optimize SQL queries, administer MySQL environments, and utilize a suite of tools to improve the performance of MySQL applications. It will allow you to perform tasks such as creating and viewing databases and objects (triggers or stored procedures, e.g.), configure servers and much more. You can easily perform backup and recovery as well as inspect audit data. MySQL Workbench will also help in database migration and is a complete solution for analysts working in relational database management and companies that need to keep their databases clean and effective.
STANDALONE PREDICTIVE ANALYTICS TOOLS
Predictive analytics is one of the advanced techniques, used by analysts that combine data mining, machine learning, predictive modeling, and artificial intelligence to predict future events, and it deserves a special place in our list of data analysis tools as its popularity increases in recent years with the introduction of smart solutions that enabled analysts to simplify their predictive analytics processes. You should keep in mind that some BI tools we already discussed in this list offer easy to use, built-in predictive analytics solutions but, in this section, we focus on standalone, advanced predictive analytics that companies use for various reasons, from detecting fraud with the help of pattern detection to optimizing marketing campaigns by analyzing consumers’ behavior and purchases. Here we will list a data analysis software that is helpful for predictive analytics processes and helps analysts to predict future scenarios.
SAS FORECASTING
KEY FEATURES:
Automatic forecasting for a large number of entities or products, including hierarchical forecasting
Scalability and modeling by combining 2 or more models and creating an ensemble
An unlimited model repository that includes time series and casual methods such as ARIMA and ARIMAX
SAS Forecasting for Desktop has established itself as one of the most prominent advanced data analysis software that offers a wide range of forecasting methods, including hierarchical reconciliation, event modeling, what-if analysis, and scenario planning. Their features comprise 7 core areas of forecasting processes, some of them we already mentioned: automatic forecasting, scalability and modeling, unlimited model repository, easy-to-use GUI, event-modeling console, what-if analysis, and data preparation. Based on the variables that you enter in the modeling process, SAS will automatically select variables to generate forecasts to unravel what happens in your business.
Moreover, with a bundle of the SAS Forecast Server, and Visual Forecasting solutions, this data software enables users to produce a large number of forecasts, and automate their processes. Since the company is on the market for decades, they have established themselves as an authority figure in predictive analytics, and it certainly makes sense to give them a try.
Conclusion
Because companies can be exposed to fines and risk lawsuits for discovering data breaches or other fraudulent acts after the fact, proactive auditing is a good tactic. The right data analytics software can help companies audit their data in a variety of ways.