Best Data Analysis Tools for 2020

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Data is the currency of the future, and in order to get the most out of their data, businesses need to be able to access and make use of their data. Luckily, there are literally hundreds of amazing business analytics tools on the market that make quick work of the complicated tasks required to capitalize on this data. Unfortunately, these hundreds of available tools can cause choice paralysis. How do you choose the best data analysis tools from all these options?

This article aims to answer that question by providing a list of the top data analysis tools this year, as well as some helpful tools for users looking to find their personal best match. So let’s get started!

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Top Data Analysis Tools

Key Data Analysis Tool Features

Before you can choose the right tool, you have to know what to look for. While many tools offer unique features, there are some basic requirements buyers can expect to find in data analytics tools. Here’s a quick rundown:

Data Discovery

Data discovery is the process of exploring, processing, collecting, cleaning, consolidating and generally preparing it for analysis by algorithms or analysts. It includes real-time in-memory processing, visual data interaction and other preparatory features. This step also begins the process of discovering trends for future analysis by highlighting patterns in the data.

Data Visualization

To gain insights from data, it’s important to be able to visualize patterns in more visible ways than simply viewing tables of numbers. That’s where data visualization comes in. Through functions like storyboarding, animations, auto-charting, plugins and geospatial interaction, users can view datasets in an easy-to-understand graphical representation.

Data Analytics

After visualizing and prepping data, it’s time to perform analytics to draw conclusions. Using ad-hoc analytics, users can answer a specific business question by running an on-demand report for a single metric. Predictive analytics forecasts future outcomes based on previous data to help with planning and predictions. Diagnostic analytics identify problems and pain points within datasets, and prescriptive analytics suggests how to solve them.

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Advanced Analytics

Advanced or augmented analytics uses cutting-edge artificial intelligence, machine learning, natural language processing and other technologies to examine data in previously impossible ways. Users can perform text analytics to draw information from unstructured textual data such as surveys or user comments on posts, crunch big data sets, perform web analytics, draw data from social media and more.

Reporting

Reporting involves gathering information on an organization’s operations and compiling insights based on that information into easily-digestible formats for collaboration and communication with key stakeholders. Data analysis tools typically offer dashboards, information sharing, ad-hoc reporting and other types of reporting capabilities.

Integrations

Another crucial thing to keep in mind when seeking a data analytics tool is what it will have to integrate with. Integrations can include the other software solutions an organization uses, what data sources data will be drawn from, productivity and communication tools like MS Office, Gsuite and Slack, as well as web services. Not all data analytics software tools can integrate with every kind of application, so make sure to clarify these needs up front when choosing a solution.

Data Analytics Tool Requirements

 

Now that you know what to expect, let’s dive into the best tools for data analysis functionality.

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Top Data Analysis Tools

Tableau

As one of the largest names in business analytics, it should be no surprise to find Tableau on this list. Users can perform self-service business intelligence tasks such as explore data, create visualizations, share insights and collaborate on reports. It can be customized to suit any organization’s needs and comes in SaaS, server and big data-specialized formats.

Tableau Data Analysis Tool

 

The following features are what make Tableau a leading data analytics tool:

Real-Time Data

Tableau connects to a variety of data sources such as BigQuery and Amazon Redshift as well as web apps like Salesforce or Google Analytics. Tableau Bridge pulls data from behind firewalls and publishes on-premise published data at pre-set intervals, allowing report generation and exploration with up-to-the-minute information regardless of data source.

Interactive Elements

Dashboards present data in intuitive visual forms and allow users to drill down, filter and highlight data points as they explore. Built-in geographic features let users plot data on maps based on geospatial information such as region names, population data, demographics, airport codes and geocodes. Users can also customize their views and author workbooks through the web editing tool.

Native Mobile App

Native iOS and Android apps let users interact with data as well as securely share visualizations and reports from their mobile devices.

Security for Every Level

Role-based access allows all users to interact with data approved for their position. The system is built on multi-tenant architecture that partitions users and data by client and allows for customization of each instance of the tool. All data is secured with row level security (RLS) that restricts access to workbook rows based on user roles.

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Time-Series Analysis

Create time-sensitive reports with the drag-and-drop wizard to analyze time-related trends such as day of the week, year-by-year, moving averages and more. Perform live queries or pre-schedule data extraction to keep data fresh.

Augmented Data Prep

The tool makes smart data cleaning recommendations based on machine learning algorithms. It suggests changes to standardize and clean common data irregularities by filtering, applying data roles, trimming space, replacing values and more.

Qlik Sense

Qlik Sense from Qlik is a tool for augmented data analytics and business intelligence. It offers a robust suite of tools that let users interact with data through a gesture-based touch UX. It keeps data secure with row- and column-level security as well as a rules-based security model. Some of Qlik Sense’s companion products include Qlikview and Qlik Big Data.

Qlik Data Analytics Tool

 

These features make Qlik one of the best data analysis tools:

Associative Engine

Index all possible relationships between data sets to discover patterns and glean insights. Unlike query-based BI tools, Qlik Sense is not limited to predefined queries from a pre-aggregated database, opening up many data exploration options for users.

Advanced Analytics

Qlik Insight Bot lets users perform NLQ searches and conversational analysis powered by artificial intelligence to ask questions and get answers quickly. Advanced analytics integration APIs let users draw and exchange data with third-party tools like R or Python to make predictive calculations and explore data in real time.

Visualizations

Users can easily create customized or standard reports in a drag-and-drop dashboard, then schedule and deliver them via email, share them to collaborative folders or publish to a web platform through Qlik NPrinting. If static reports don’t cut it, Qlik Sense offers interactive visualizations like charts, tables and other objects to display data while letting users engage with it through various exploration actions.

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Insights

The insight advisor uses the Qlik cognitive engine to suggest the best format in which to display each dataset based on data traits such as behavior, feedback, patterns and industry trends. Analysts can utilize this feature to more effectively identify insights from data as well as capture, organize and share them.

Storyboards

The data storytelling feature gives users guidelines to create and share visually engaging data narratives by combining reports, visualizations, exploratory analysis, collaboration and presentation formats.

Embedded Analytics

From simple widgets to fully embedded applications, Qlik Sense makes it easy to integrate disparate systems in order to most effectively perform analytics within optimal workflows.

SAS Visual Analytics

SAS is one of the industry leaders for business tools, and analytics is no exception. It provides a range of BI products, including SAS Enterprise BI Server, SAS High-Performance Analytics, SAS Social Media Analytics and SAS Business Analytics. SAS Visual Analytics combines high-speed, high-volume data processing with advanced analytics and query-based reporting tools to provide a dynamic self-service BI solution.

SAS Visual Analytics Tool

 

SAS Visual Analytics offers one of the best data analysis tool options because of the following features:

Self-Service Data Preparation

Import data, join tables, apply functions and generate columns to explore data with a drag-and-drop interface for easy data preparation. Dynamic group-by processing concurrently builds models for individual segments without requiring users to sort or index data each time.

Text Analysis

Collect, clean and organize large volumes of unstructured text data from sources like social media to gain customer insights, brand sentiment, demographic trends and more.

Location Analytics

Combining traditional datasources with locational data allows SAS to perform geographically contextualized analysis. Esri ArcGIS and OpenStreetMap let users lasso data points on maps to highlight and select data for analysis as well as add map pins to record points of interest.

Augmented Analytics

SAS Visual Analytics detects patterns between data using machine learning algorithms, NLP, statistical techniques and topic detection. Auto-charting features choose the best-suited visualization format to display chosen data.

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Predictive Modeling

Using augmented analytics techniques, the tool builds predictive models via both visual and programming interfaces. It offers k-means clustering, scatter plots and detailed summary statistics to promote detailed data exploration.

Distributed Processing

SAS Cloud Analytics Services is a Viya server that performs processing tasks and then distributes them across nodes in clusters. The results of data processing is held in the memory indefinitely across both job and user boundaries to reduce latency issues.

Oracle Analytics Cloud

Oracle provides one of the most extensive and versatile collection of business intelligence and analytics tools on the market, including the following products: Oracle Database, Oracle BI, Oracle Big Data SQL, Oracle BPM, Oracle Reports, Oracle Discoverer, Oracle Endeca, Oracle Essbase, Oracle BI Cloud and more.

Oracle Analytics Cloud offers web-based self-service data analysis capabilities that empower users to perform AI-assisted data preparation, reporting, analysis, service management and automated lifecycle management tasks in the cloud.

Oracle Analytics Cloud Tool

Connect and Prep Data

Choose from over 50 data connectors in order to draw data from a variety of sources into a cohesive data warehouse. The system then structures and cleanses the data to prepare it for analysis. The smart cleaning feature recommends the best way to cleanse data and eliminate outliers in order to generate the best visualization.

Dashboards

Create, manage and interact with personalized visual dashboards that summarize data from a variety of sources. Users can apply filters, search data and build dashboards by dragging and dropping desired features. These dashboards can be viewed online, exported or printed.

AI-Assisted Analytics

Oracle Analytics Cloud supports AI-augmented analytics that deliver automated descriptive analysis, key driver analysis, automatic segmenting and clustering, as well as automated forecasts. It uses machine learning to autonomously identify patterns and trends, then displays them in the best match visualization.

Collaborative Sharing

A multidimensional engine lets users initiate collaboration on reports, visualizations and dashboards via email or on the interface itself through commenting. These collaborations can be easily captured along with analysis for future use.

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What-If Scenario Modeling

Oracle Analytics Cloud uses the native multidimensional analysis engine Oracle Essbase to perform predictive modeling. Users can create individual what-if scenarios to make more accurate forecasts based on historical data.

Data On the Go

The free Oracle Synopsis app lets users engage with data, edit spreadsheets and interact with business data from their mobile device. It offers smart summaries, filtering, sorting, automated chart generation zooming, fingerprint access, on-device analytics and more. Oracle Day by Day is an app that provides a smart feed that auto-refreshes to deliver a constant stream of analytics and data to users. It performs query-based data searches as well as collaborative sharing.

Board

BOARD combines BI, EPM, BA, CPM and data discovery into a single powerful tool that comes with multi-language support to cater to many global users. It enables file attachment so images can be implanted in tables and associated with specific cells.

Board Data Analysis Tool

Multilevel Data Navigation

Users can explore data in multiple dimensions as they drill down, drill through and zoom out. The BOARD capsule feature lets users group items and contain them for easier access as well as equip them with folders, filters and navigation menus. It offers both iOS and Windows mobile apps.

Privatized Access

Individual users can choose any graph or report and customize, save or share it via a private virtual pinboard, creating a custom personal view of relevant visualizations. Cell-level security keeps data access role-based and can be personalized for unique users.

Data Fast Track

BOARD Fast Track is a self-service BI module that connects to data at its source and draws it to the operational database, allowing users to run modeling functions and visualize data without IT support. A reverse algorithm lets users make batch changes across datasets to indicated fields, and real-time data modeling capabilities let them change models during planning or forecasting without affecting the data source.

Analytical Functions

BOARD version 10 offers out-of-the-box statistical functions that include min/max, averages, standard deviation algorithms and more to facilitate data analysis. It incorporates Excel formulas into tabular reports and replicates the logic applied to the data in the spreadsheets for on-the-fly metric calculations. Run simulations and create scenarios to predict the outcomes of different events before decision-making.

Scorecards

Translate company strategy and best practices directly into meaningful maps and scorecards to communicate and track implementation. Management can roll out objectives across departments simultaneously and monitor execution from a centralized hub. It also highlights patterns that affect scorecard elements and understand what dynamics affect KPIs.

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Conclusion

While these five tools offer the best data analysis functionality, that doesn’t necessarily mean they’ll be the best for your unique business needs. This interactive requirements template can help you identify which features of data analysis tools are the highest priority for your business, and which you might not use. Then head over to our comparison matrix to see how different options stack up based on your specific requirements. And don’t forget to check out our price guide for detailed pricing information on these and many other business analytics solutions.

Do you agree with our analysts’ list of top data analysis tools? Which tools would you include and why? Let us know in the comments!

Bergen AdairBest Data Analysis Tools for 2020

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