illustration of Big Data Analytic Tool on a screen with charts and graphs

10 Best Big Data Analytics Tools For Reporting In 2021

Software and digital professionals are used to massive amounts of real-time data coming at us from all angles. We’re also keenly aware of how important it is to turn data lakes into readable, actionable insights that can fuel future business decisions.

IIA Director of Research Tom Davenport interviewed 50+ businesses and found the most common uses of big data are cost reduction, faster decision making, and innovation of new products or services. There is an obvious incentive for high impact enterprise data wrangling. That’s why it’s imperative that you pick the absolute best big data processing and analytics tool for your unique situation.

Deciding “how” and “with what” to navigate your complex data optimization is tough. That’s why I’ve compiled this list of advanced analytics solutions that can be leveraged to spin your data sources into strategy gold, so to speak.

How Is Big Data Analyzed?

To put it simply: Big data is analyzed by collecting structured semi-structured and unstructured data from your data lakes and parsing out what’s most relevant to your current informational need most likely using some form of data quality automation to do so.

Then, you leverage statistics and machine learning to parse through the data ecosystem and compile predictive analytics, user behavior analytics, and other metrics. This process might also include text analytics, natural language processing, predictive analytics, and so forth.

All of this works to create end reports that are readable and actionable for business users.

Best Big Data Analytics Tools List

Here’s a shortlist of the best big data analytics tools:

  1. Azure Data Lake Analytics
  2. IBM Cloud Pak for Data
  3. Tableau
  4. Zoho Analytics
  5. Splunk
  6. SAS Visual Analytics
  7. Arcadia Enterprise
  8. Qrvey
  9. GoodData
  10. Qlik Sense

Big Data Analytics Tools Comparison Criteria

Here’s a summary of my evaluation criteria: 

  1. User Interface (UI): Does the software convey large, complex data sets stemming from myriad sources in an easy to understand, intuitive, and efficient way? Can users reasonably find their way around the large-scope data technologies?
  2. Usability: Big data analysis comes in many shapes and does many things—does the big data software offer use case-specific tutorials, training resources, and tech support? Is the full functionality of the tool manageable for motivated data science experts?
  3. Integrations: Big data analytics tools must connect to an assortment of common and uncommon data stores—Hive, Oracle, Azure, Google Cloud, and social media. There are some must-haves; for example, easy connectors with Amazon Web Services (AWS).
  4. Value for $: Pricing of big data processing solutions must be scalable according to the amount of data, number of data warehouses, artificial intelligence capabilities, and other metrics. Are all costs fair, transparent, and flexible?

Big Data Analytics Tools Key Features

  1. Inclusive of a variety of programming models, like MapReduce, Message Passing, Directed Acyclic Graph, Workflow, SQL-like, and Bulk Synchronous Parallel
  2. Statistical algorithms and what-if analysis
  3. Flexible programming language accommodations (ex. SQL and NoSQL, Java, Python)
  4. A streamlined, interactive application programming interface software (APIS)

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Overviews Of The 10 Best Big Data Analytics Tools

Here’s a brief description of each big data analytics platform on my list, showcasing what it does best, plus screenshots to showcase some of the features.

1. Azure Data Lake Analytics – Best pay-per-job big data solution

Screenshot Of Azure Data Lake Analytics
Develop parallel data transformation and processing programs in U-SQL, R, Python, and .NET.

Azure Data Lake Analytics is an on-demand analytics job service that prices per-job, ensuring that you only pay for the processing as you use it. This tool can process petabytes of data for business intelligence (BI) as well as sentiment analysis. You’re left with high-impact visualizations of your relational source data, such as Azure SQL Database and Azure Synapse Analytics.

Azure Data Lake Analytics costs from $1 per 1,000 runs or $0.25/DIU-hour and scales according to your use case.

Pros:

  • Simple solution for batch workloads
  • Complimentary storage of relational database and NoSQL 
  • Works well with power BI services for reporting
  • Only pay for consumed ADLUs

Cons:

  • Lack of streaming option and event processing
  • May be confusing for users coming from a primarily MSBI background
  • Lacks resources for end-user training

2. IBM Cloud Pak for Data – Best for reducing ETL requests

Screenshot Of IBM Cloud Pak for Data
Access a range of big data solutions, like self-service analytics and machine learning.

IBM Cloud Pak for Data is a fully-integrated, cloud native, data and AI platform designed for sophisticated DataOps and business analytics solutions. IBM boasts a potential for a 25-65% reduction in extract, transform, load (ETL) requests by eliminating the complexities of data integration of different data types and structures using Cloud Pak for Data. You can customize your workflow using their flexible API and complimentary proprietary and third-party services.

IBM Cloud Pak for Data costs from $800/month and offers a 7-day free trial.

Pros:

  • Award-winning data security solutions 
  • Good for optimizing storage and other maintenance of preexisting data
  • Tailored solutions for lessening your ETL request load

Cons:

  • Could use more options to better migrate data from other cloud providers to IBM 
  • May be cost prohibitive for smaller enterprises 
  • Their Db2 database has a bit of a clunky, old-fashioned feel

3. Tableau  – Best big data analytics tool for ease of use

Screenshot Of Tableau
Interactive data visualization presented across easy-to-build maps and charts.

Tableau is a user-friendly, intuitive visual analytics platform with built-in best practices for data exploration and informational storytelling. Users can access their full suite of self-service prep and analytics tools with a minimal learning curve, leveraging drag-and-drop visualizations and easy point-and-click AI-driven statistical modeling. Most users should be able to assemble data to their liking without advanced programming or special commands.

Tableau costs from $70/user/month and offers a free 14-day trial.

Pros:

  • Good native integration with Salesforce CRM
  • Comes with robust mobile app for iOS and Android
  • Offers a hearty variety of chart types (Sankey, Doughnut, Maps)
  • Easy to use with self-learning module available

Cons:

  • Some data manipulation required in order to successfully match queries 
  • Limited room for columns when assembling worksheets 
  • Frequently requires saved database connections to be re-authenticated

4. Zoho Analytics – Best free data analytics tool

Screenshot Of Zoho Analytics
Turn raw data into interactive, easy-to-read maps, charts, and graphs.

Zoho Analytics is a self-service BI and analytics software used by the likes of Hyundai, Ikea, HP, and Philips. Their freemium plan is a bit feature lite but you can add up to 2 users, input up to 10K rows/records, and access unlimited reports and dashboards. This is a pretty sturdy offering for free-to-use data analysis. Zoho Analytics comes with a library of pre-built visualizations divided by function (social media, finance, IT, sales) to help you get started. 

Zoho Analytics costs from $22/month for 2 users and offers a free 15-day trial. They also have a free plan for 10K rows/records or less. 

Pros:

  • Building or customizing reports and dashboards is super easy 
  • Excellent embedded AI feature (called ZIA) 
  • Generate reports right from SQL queries 
  • Feature expansion through connection with Zoho’s other apps

Cons:

  • Hourly data sync not included in entry level plan 
  • Cannot auto export data straight to Google Drive 
  • Dashboards seem a bit cramped and busy

5. Splunk – Best for user behavior analytics

Screenshot Of Splunk
Tab through scenario-specific reports like app delivery, security, executive view, and IoT.

Splunk is currently used by 91 of the Fortune 100 companies, including Intel, Comcast, and Coca-Cola. Splunk offers machine learning-centric visibility and detection of entity profiling and scoring, risk behavior detection, anomaly observation, and high fidelity behavior-based alerts. You can access a free cloud-based sandbox trial of Splunk UBA to check it out before committing. They offer dedicated solutions to DevOps, Security, IT, and big data. 

Splunk costs from $2000/year for 1 GB/day and offers a free plan that allows you to index only 500 MB/day.

Pros:

  • Flexible data and report sharing using URL links 
  • Quick log queries across different types of infrastructure
  • Search queries can be saved for repeat use or converted into apps 
  • Can set up detailed, specific alerts for various KPIs

Cons:

  • Infrastructure maintenance requires more manpower than some competitors 
  • Query builder may be prohibitive for non-technical users 
  • Steep learning curve compared to others

6. SAS Visual Analytics – Best big data analytics tool with smart visualizations

Screenshot Of SAS Visual Analytics
Transform your raw data into any visualization with high quality-of-life flexibility.

With SAS Visual Analytics, users are able to easily import data from databases, Hadoop, Excel spreadsheets, and social media. They offer a huge variety of interactive visualizations, including bar and pie charts, heat maps, animated bubble charts, vector maps, numeric series, tree maps, network diagrams, correlation matrix, forecasting, decision trees, and more. Plus they have ease-of-use options like one-click filtering and automated content linking. 

SAS Visual Analytics costs from $8000/year and offers a free 14-day trial.

Pros:

  • Flexible drag-and-drop analytics elements 
  • Well-suited to support high volume of simultaneous users 
  • Works with tens of millions of records without lagging 
  • Quality BI dashboards can be accessed across many devices

Cons:

  • Low number of connection options with third-party apps 
  • Could use better HTML5 support
  • May be price prohibitive compared to others on this list 

7. Arcadia Enterprise – Best telecommunications analytics solution

Screenshot Of Arcadia Enterprise
 AI-driven data lake analytics and BI software that runs natively within modern data platforms.

Arcadia Data scored first place in the 2018 Big Data Analytics Market Study by Dresner Advisory Service report among 17 other BI vendors. Their in-data-lake BI architecture offers a drag-and-drop web-based interface, an in-cluster analytics engine that scales linearly for ease of management, and embedded analytics for Hadoop and Cloud. Telecom companies will enjoy their behavioral churn analysis, service cost controls, and impact of infrastructure reports.

Arcadia Enterprise offers customized pricing upon request. They also have Arcadia Instant, a freemium version of their tool whereby processing is done on your computer rather than on a server cluster. 

Pros:

  • Freemium tool is very accessible and great to test the software 
  • Smooth, intuitive interface for data connections and dashboards 
  • Handy scheduled mail reporting features

Cons:

  • Poor integration with Hortonworks Data Platform
  • No mobile app available at this time 
  • A steep learning curve for IoT analytics and ingest functionality

8. Qrvey – Best big data analysis for start-ups

Screenshot Of Qrvey
Enable your team to build aesthetic and feature-rich dashboards, charts, and reports.

Qrvey is an embedded analytics platform used for SaaS data, analytics, and automation technologies. You can deploy it right into your pre-existing AWS account in order to visualize your entire data pipeline. Their start-ups package includes specialized support for pre-launch or early-launch companies, like quick installation and launch, serverless analytics scalability, no-code embedded widgets, up to 10 GB data, and a lower entry subscription price point.

Qrvey costs from $2500/year and offers both a free demo and a free trial. 

Pros:

  • Good out-of-the-box workflows/automation tool
  • Ability to embed a chart into your own web app without iFrames
  • Unlimited users and API calls for ever plan tier 

Cons:

  • Unlimited data limited to highest tier subscription plan 
  • Few online resources available for self-help 
  • More chart types would be welcomed 

9. GoodData – Best agile data warehousing

Screenshot Of GoodData
Easily build your own data pipeline and design your own logical data model.

GoodData is a big data analytics platform that provides users the tools, runtimes, and storage for data ingestion, preparation, transformation, and analytic queries. They boast 50+ connectors for data ingestion/synchronization and offer an Agile data warehousing system on higher tier plans. Their per-workspace pricing model lets unlimited users access sets of data models, metrics, calculations, and dashboards according to a flexible permissions system.

GoodData costs from $20/workspace/month and offers a free demo. They also have a free plan that includes 5 workspaces and up to 100 MB/workspace.

Pros:

  • Non-technical users can build dashboards and views easily 
  • Excellent integration with Salesforce, Pardot, Zendesk
  • Good for scheduling reports according to exact times and frequencies 
  • Provides easy linking of disparate data sources for comparison 

Cons:

  • Coding knowledge required for inquiries and report building 
  • Datasets of 100M+ rows may stall performance 
  • Some data model adjustments might require customer support

10. Qlik Sense – Best big data analytics tool for purchasing departments

Screenshot Of Qlik Sense
Freely analyze data without pre-aggregated data or predefined queries.

Qlik Sense is an end-to-end data analytics platform with a unique associative analytics engine that lets users search and explore across all data in any direction with no pre-aggregated data or predefined queries to limit you. Purchasing departments will get the most use out of in-depth supplier and industry trend comparisons, easy currency filters for international partners, and low product or low spend reports. 

Qlik Sense costs from $30/user/month and offers a free 30-day trial. 

Pros:

  • Thorough and quick search functionality 
  • Incorporated data modeling for “no-warehouse” options 
  • Easy to reuse code or query logic for time saving 
  • Low learning curve for self-service

Cons:

  • Not as customizable as others, like Tableau 
  • Minimal non-interactive report creation options 
  • Low res monitors may struggle to clearly display some reports

Free Big Data Analytics Tools

Big data analytics usually comes with a cost. These slimmed down versions of data processing and analysis are free to use, though.

  1. Zoho Analytics – Free plan for up to 2 users and 10K rows/records or less
  2. Kognito – Free if deployed on standalone servers or on MapR but limited to 512GB RAM.
  3. Splunk – Free with limited enterprise features and a limit of indexing 500 MB/day.
  4. Arcadia Instant – Free downloadable option with all processing done on your computer rather than on a server cluster.
  5. GoodData – Free plan includes 5 workspaces and up to 100 MB/workspace.

Other Big Data Analytics Tools

Here’s a few more that didn’t make the top list.

  1. DNIF Big Data Analytics – Best event log management 
  2. CloudMoyo – Best for CIOs and CTOs
  3. Altamira Lumify – Best for link analysis 
  4. Azure Databricks – Best for Microsoft Suite users 
  5. MATLAB – Best iterative analysis and design processes
  6. Qubole – Best for openness and data workload flexibility
  7. SiSense – Best API-first cloud technology
  8. Apache Spark – Best open-source big data analytics tool (with Apache Hadoop)
  9. Talend – Best data integration with governance
  10. Plotly – Best to productionize Python analytics
  11. Cloudera – Best industrialized enterprise AI
  12. Jethro – Best for 1000+ concurrent users 
  13. Exasol – Best for retail data analytics
  14. Omniscope Evo – Best for Chrome browser users 
  15. Deep.BI – Best for e-commerce and banking
  16. Accelerite ShareInsights – Best collaborative rapid insight prototyping 
  17. Bizintel360 – Best for analytics without programming knowledge
  18. iCEDQ – Best for dataops testing and monitoring 
  19. Hortonworks – Best open source framework for distributed storage 

Which Big Data Analytics Tools Have You Used?

What do you think about this list of business intelligence and big data analysis tools? What data management tools do you use for your business analytics on a day to day basis? Do you have a big data platform in mind that you would add to this list if you could? What big data visualization tools are your “must-haves” on-premise or in the cloud? Let us know in the comments section.

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