14 Tools for Data Analysis
Today’s data analysis process is more than gathering and processing information. It encompasses arranging and explaining data as well as making conclusions to draw an objective and itemized picture of where the business is heading. And while 20 years ago it was a very time-consuming process, modern analysis tools allow for better efficiency as well as greater insight into the business processes.
The ultimate significance of data analysis is the ability to track the progress and changes in your business performance. This information serves a reliable foundation for informed business decisions to achieve further development. In other words, using data analysis is crucial for business success. Based on the current projections, the importance of business data analytics will only grow. Below you will find the list of tools that will help you retrieve, explore, visualize, and analyze data to have a greater insight into how your business is doing.
Tableau strives to ensure maximum functionality, fast speed, and excellent visualization. Its ability to connect to various local and cloud-based sources makes Tableau one of the most popular data analytics tools. Additionally, its intuitive interface makes it easy for all users to source, prepare, explore, analyze, and present data in a streamlined workflow.
Depending on the type of analytics, its users can use Tableau Server to house recurring reports, utilize the integrated functionality for self-service programs via Power User feature, and seamlessly add Tableau analytics into a business application through application integration technologies. Apart from its flexibility and functionality, Tableau is one of the best programs to use if you are after simple yet attractive visualization.
Looker is a cloud-based platform focused on providing a unified data management environment for business intelligence, analytics, and visualizations. Technically acute users will find Looker’s reusable components, as well as modeling data features, extremely useful.
Its LookLM language allows creating mini-applications as it exploits SQL in a reusable way (don’t worry if you don’t know SQL – Looker has great tutorials). Looker’s Blocks is another handy tool to be used for data connections, analysis, and distribution (the great thing is that its components are reusable as well!). This could-based platform is an excellent solution for those who value the robust security of data in combination with customized solutions and integrations.
If you are looking for data analytics tools that could be easily integrated with the most popular ERP systems, Solver is the one to go with. Apart from its out-of-the-box integration opportunities, it also offers intuitive modules for forecasting, budgeting, data warehousing, reporting, and consolidations. Solver strives to provide easy-to-use tools for finance professionals in a wide range of presentation environments.
Solver’s BI360 contains industry-specific templates which makes it easy for professionals to contextualize data, budgets, and presentations. Its enriched dashboard allows generating reports in a variety of formats as well as it can visualize the data accordingly based on the created reports. It is available both for on-premise deployment and as a cloud-based solution.
Dataiku DSS is a complex data science software made to simplify the data analysis process as it features the entire lifecycle in one place. Apart from supporting Engineering, Finance, and Marketing projects, Dataiku DSS can help non-technical users build sustained data products and facilitate the digital transformation of their business.
The great thing about this data analytics tool is that it offers integration to over 30 connectors and has customized plug-in extensions to link users to their systems. It also enables users to source data, build projections, develop various visualizations, and collaborate with other users. If you are after a deep analysis, such as demand forecasting, lifetime value optimization, church analytics, then Dataiku is one of the best options available.
KNIME was built to make the life of data scientists easier. Its ability to design data science applications as well as create machine learning models make it an advanced data analysis tool. With a heavy emphasis on statistical models, KNIME’s nodes will help to easily manage every aspect of data analysis, from extraction to the presentation.
This platform can integrate with such tools as Hadoop, R, H2O, and Python. It can also integrate with both structured and unstructured types of data. The distinctive feature of KNIME is supporting media sentiment analysis, market basket analysis, medical claim outline detection, and text mining.
With built-in security controls and centralized workflow management, RapidMiner is another quality tool to manage and analyze complex data. Its automated machine learning feature helps analysts and data scientists to improve their productivity and speed up the process. The tool will help data scientists and non-technical users alike enhance their efficiency through automated machine learning. RapidMiner Radoop will help you manage data effectively without writing the code. The tool integrates with R and Python, automating predictive modeling, data prep, and what-if gaming.
Overall, it is a great platform for data preparation, text mining, predictive modeling, and machine learning. RapidMiner’s unique features are machine learning, team collaboration, contextualized recommendations, and automated parameter selection.
Supporting Linux, Mac, and Windows operating systems, Pentaho is a great business intelligence tool focusing on IoT data. It can work together with Customer Relations Management (CRM) systems and Enterprise Resource Planning (ERP) systems for better insight. Additionally, Pentaho allows blending with such data giants as Hadoop and NoSQL.
One of the greatest things about Pentaho is its data collection speed along with the visualization capabilities. This business intelligence software also offers embedded analytics to ensure customer success which is a rare case among similar tools.
Talend was built to integrate data faster without compromising the ultimate value. Available as an on-premise solution and a cloud-based platform, it works with Google Cloud, Snowflake, Azure, and AWS. This tool offers unique functionality allowing users to enjoy its self-service data preparation. Its integrated toolset makes data preparation easier for those who need the context. The reduced time to merge different data sources makes Talend a great option for most business users.
Domo was built to help non-technical users manage data faster. This data management tool provides over 500 data connectors allowing you to connect with the other sources from the propriety systems, cloud platforms, and on-premises systems. Domo simplifies a lot of data management processes and makes the entire journey much faster due to its robust business intelligence capabilities, embedding analytics, and native mobile devise support.
Designed to manage all sorts of data, Sisense is different from the traditional data analysis tools available on the market today. It has a strong governance component; its technology deploys parallel processing and an in-memory columnar database allowing for the safe accumulation of big data sets. Many users enjoy its visual data sourcing and notification alerts.
Sisense is famous for its robust approach to embedded analytics allowing its users to customize visualizations.
Automating data discovery and optimizing data acquisition/preparation processes, Qlik is famous for its speed to insight characteristics. It also automates relationships between data sources which helps make the process more efficient. Due to the associative engine and its data profiling methods, Qlik can present combined data sets very quickly. But this tool isn’t only about speed and automated processes. Qlik makes data exploration a smooth experience, mostly due to its in-memory processing system.
Microstrategy was created back in 1989 which makes it one of the oldest data analysis tools. Years of experience has made this platform a mature player on the market of data analytics platforms.
As you would expect, Microstrategy can connect to ERPs and cloud data vendors in additional to traditional integrations with Android, Windows, and iOS user clients. As a big player, Microstrategy also offers a wide range of useful services, such as security, alerts, BI functions, distribution, etc. This data analysis software uses end-point telemetry to improve data governance and optimize user access. Overall, Microstrategy is a solid tool with robust security practices, enhanced functionality, and a strong toolset.
If you like a conversational approach to data processing and analytics, then Thoghtspot must be the right tool for you. The conversational analysis is enabled by Thoughtspot’s interface and AI tools – SpotIQ engine can parse search requests (i.e. “income by states in 2016”) and deliver an appealing visualization based on the results (which can be sorted).
This platform features a unique data sourcing and preparation approach as well as comprehensive in-memory processing and built-in embeddable components. However, just like with other data analysis tools, you must have a solid understanding of how you want to use this product. Having qualified tech support on your team will help transform the data into the product effectively.
Birst is designed to connect various teams via shared data networks empowering business users with simple tools for better decisions. This particular platform places a big emphasis on accelerating the delivery of trusted analytics, which is one of the biggest challenges in BI.
Birst’s Automated Data Refinement for data extraction and powerful self-service analytics make this tool a must-try, especially if you need to prepare analytics without any IT intervention.