Best Data Preparation Software
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PRODUCTS
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BUYER'S GUIDE
Buyer's Guide
By Payal Tikait, Technical Content Writer at SelectHub
Data preparation software's primary objective is to clean raw data and use it in business intelligence applications for further analysis.
Data preparation involves:
- Enriching and optimizing information by blending internal and external datasets.
- Creating new fields.
- Addressing inconsistencies.
- Replacing missing values and eliminating duplicate data.
Data preparation solutions are crucial for big data analysis that deals with inconsistent information.
Executive Summary
- Data preparation software extracts, blends, cleanses and transforms data for advanced analysis.
- It offers robust data access, governance and modeling features.
- It provides pay-per-user and perpetual license pricing models.
What This Guide Covers:
What Is Data Preparation Software?
These tools extract, blend, combine, cleanse, transform and organize data for analysis via the following steps:
Data Preparation Steps
- Data Collection: Gather data from multiple sources like operational systems, data warehouses, lakes and more. During the collection phase, users need to identify data types, sources and methods to ensure information quality and integrity.
- Data Discovery and Profiling: Explore the data to identify patterns, relationships, outliers, inconsistencies, anomalies and missing values. Create data profiles, gauge information and address issues to avoid skewing analysis outcomes.
- Data Cleaning: Identify data errors to create complete and accurate datasets. While cleaning databases, it is essential to identify and replace missing values, remove outliers and harmonize inconsistent entries.
- Data Structuring: Model and organize data for further analysis. For instance, convert data stored in CSV files into tables to make it accessible for BI tools and applications.
- Data Transformation: Transform data into a unified and usable format. For example, create aggregated fields or columns from existing entries. Optimize datasets by augmenting and adding data.
- Data Validation and Publishing: Run automated routines to validate data for consistency, accuracy and completeness. Store prepared data in data warehouses, lakes or any other repository for advanced analysis.
Primary Benefits
Data preparation software offers the following benefits:
- Ensures that information used in analysis produces robust and reliable results.
- Notices and fixes issues that may otherwise go undetected.
- Enables business executives to make informed decisions.
- Provides higher ROI from BI initiatives.
- Reduces data management costs.
Key Features & Functionality
Data Access | Access unstructured, semi-structured and structured data from different sources. |
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Data Blending | Combine multiple sources into a coherent dataset to reveal valuable insights. Users can blend the data using relationships or joins. |
Data Transformation | Convert raw data into usable information by transforming data types, eliminating outliers, removing duplicate data, correcting typos and normalizing numerical values into standard forms. |
Data Modeling | Identify data types and their relationships with each other. Specify grouping methods, formats and attributes. |
Data Governance | Use protection features such as encryption, authentication, user permission and security filtering at individual/group/role levels. |
Software Comparison Strategy
Consider the following factors when selecting data preparation software:
User Interface
Some data preparation tools offer an intuitive drag-and-drop interface to ingest, transform, prepare and visualize data. While others utilize some of these popular scripting languages to convey instructions, a few provide a mix of both.
If non-technical users use the tool, you may want to invest in a visual point-and-click interface. They can work directly with the data and logic instead of abstractions and workflows to accelerate the data preparation and discovery process.
Data Governance
Select a system that provides robust standards and policies for data governance. A well-crafted strategy helps organizations establish processes to protect data integrity and secure it from malicious access.
Data Profiling
When working with large data volumes, users can interact with samples to develop preparation processes and apply them to an entire dataset. However, with unfamiliar and complicated sets, samples may not include all the outliers and anomalies that exist in the complete version.
When selecting data preparation software, ensure that it works with entire datasets and not just samples. This capability will help mitigate unexpected outcomes from the samples alone.
Cost & Pricing Considerations
Pay-per-user and perpetual license pricing models are common options from most vendors. Pay-per-user options allow organizations to pay a monthly fee for each employee. A perpetual license involves paying an upfront amount for indefinite software use.
Most Popular Data Preparation Software
Let's look at some popular data preparation tools:
Hadoop
Hadoop is open-source software that stores and processes vast amounts of unstructured data like text, images and videos. It leverages distributed computing models in the form of cluster nodes to analyze information in parallel while ensuring faster processing. It integrates with big data applications such as Google Analytics, Oracle Big Data SQL, YARN, MapR and more.
Prepare and analyze data in Hadoop.
Tableau Big Data
Tableau Big Data is a visualization platform that ingests, transforms, sorts, analyzes and visualizes information to derive insights. It leverages an in-memory processing engine to execute queries efficiently. It builds responsive reports and dashboards to unearth trends, patterns and opportunities.
Leverage VizQL, a visual query language, to explore and interact with data in real time. Facilitate connections with various data infrastructures like Hadoop distributions, NoSQL databases and Spark sources.
Create an intuitive dashboard in Tableau.
Board
Board is a business analytics solution that offers interactive dashboards, data discovery, predictive analytics and enterprise performance management capabilities under the same roof. It unifies different data sources into a logical view to make robust business decisions. Leverage the drag-and-drop interface and data discovery tools to gain meaningful insights.
Translate business processes into predictive models to assess the impact of decisions on business performance.
A forecast dashboard in Board.
Questions to Ask
Use these questions as a starting point for internal conversations:
- What are the company's present and future goals?
- Who are the end-users?
- Which deployment method is suitable?
- How vital is scalability?
- Is in-house technical expertise available to deploy and maintain the solution?
Use these questions as a starting point for conversations with the vendor:
About the Software
- What data sources does the solution support?
- How easy is it to add data sources further down the line?
- Does it allow data models to scale?
- Is it user-friendly?
- Does it need customization before deployment?
About the Vendor
- How often does the vendor release updates?
- Do they offer deployment support?
- Is training included in the purchase plan?
- Which support plans are available?
- Which advanced features are available? How much do they cost?
In Conclusion
Data preparation is crucial for businesses that use or plan to use machine learning applications. It's possible to fix errors, profile data and recommend cleaning measures through augmented analytics capabilities. This buyer’s guide should serve as a jumping-off point for professionals looking to implement a data preparation solution successfully.
Products found for Data Preparation Software
Hadoop
Apache Hadoop is an open source framework for dealing with large quantities of data. It’s considered a landmark group of products in the business intelligence and data analytics space, and is comprised of several different components. It functions on basic analytics principles like distributed computing, large data processing, machine learning and more. Hadoop is part of a growing family of free, open source software (FOSS) projects from the Apache Foundation, and works well in conjunction with other third-party products.
Tableau Big Data
Tableau is a data visualization platform that can perform big data analytics. Users can leverage well-known frameworks such as Apache Hadoop, Spark and NoSQL databases to meet their data needs. It simplifies the management, sorting and analysis of information through a single, digestible dashboard. Businesses can incorporate data from all sources and visualize it in a myriad of ways to acquire insights. The vendor offers three versions — Tableau Online, Tableau Desktop and Tableau Server.
Board
Board is a robust solution that offers analytical insights, business analytics and enterprise performance management all under the same hood. It helps key players of a company improve the effectiveness of their decision making. Its customizable and interactive dashboards give enterprises the ability to see a high-level overview of their business, as well as drill down into their KPIs to assess business performance goals. It serves mid- to large-sized companies across various industries, and its programming-free toolkit helps businesses analyze and plan with a tailored, efficient approach, irrespective of technical skill levels.
Domo
Domo is a cloud-based business management suite that accelerates digital transformation for businesses of all sizes. It performs both micro and macro-level analysis to provide teams with in-depth insight into their business metrics as well as solve problems smarter and faster. It presents these analyses in interactive visualizations to make patterns obvious to users, facilitating the discovery of actionable insights. Through shared key performance indicators, users can overcome team silos and work together across departments.
Cloudera
Cloudera is a multi-environment analytics platform powered by integrated open source technologies that help users glean actionable business insights from their data, wherever it lives. With an enterprise data cloud, it puts data management at analysts’ fingertips, with the scalability and elasticity to manage any workload. It offers users transparency into the whole data lifecycle and the flexibility of customization through its open architecture. It is available on an annual subscription basis with three offerings: CDP Data Center, Enterprise Data Hub and HDP Enterprise Plus. Each edition offers different components and pricing varies based on computing power, storage space and number of nodes. The company merged with Hortonworks in 2019 to provide a comprehensive, end-to-end hybrid and multi-cloud offering.
BIRT
It’s an open-source project on Eclipse and is an acronym for Business Intelligence and Reporting Tools. It lets organizations extract and transform data for business analysis. Its Report Designer enables visual report-building within interactive dashboards. The runtime component executes the reports once ready. Embedded into a range of business interfaces, it enables custom design layout, data access and scripting to present report output over the web. It supports charts, crosstabs, using multiple data sources within the same report, re-using queries within reports and addition of custom code.
Zoomdata
Zoomdata (now discontinued) was an analytics and reporting tool that allowed users to explore and analyze large, complex datasets. It provided a simple, modern interface that maked data literacy attainable for users of all technical levels.It was designed to be scalable and embeddable through white labeling architecture. It was built on HTML5 and JavaScript, making it fully customizable. It aimed to expedite the processes of data exploration, visualization and analysis to help users make data-driven decisions.
Alteryx
The Alteryx platform is a suite of five products offering self-service statistical, predictive and spatial data analytics to achieve enterprise, financial and industrial intelligence. It allows users to create repeatable extract-transform-load workflows, with or without a programming language. Its scalable performance and deployment options enable analysis from the enterprise to big data levels. A drag-and-drop interface enables high-speed analytics and modeling, supported by a community of model developers in the vendor’s customer base. Depending on the products selected from the suite, it can perform end-to-end BI, from data harvesting from deep data pools to automated operationalizing.
Spotfire
TIBCO Spotfire is a complete business intelligence and data discovery platform that can perform various functions, including in-depth analysis and robust visual reporting, all powered by artificial intelligence. It offers data streaming technology, which can support insights with AI, big data integration, integration with the Internet of things (IoT) and more.
BigQuery
Google BigQuery is a serverless solution that can handle large volumes of data and apply standard and sophisticated analytics techniques to deliver actionable insights to users. It comes with a number of standard and unique inclusions to help technical and non-technical users perform analysis, deliver reports, create dashboards and generate insights.
MATLAB
MATLAB is a numerical computing and programming platform that enables users to develop and implement mathematical algorithms, create models and analyze data. Designed for engineers and scientists, it can be used for a range of purposes, including deep learning and machine learning, computational finance, image processing, predictive maintenance, IoT analytics and more. Built around its matrix-based programming language, it can help users run analyses on large data sets as well as design and rigorously test models. It is available through on-premise installation on Windows and Mac. For eligible licensees, there is also a SaaS version accessible through a web browser. Users can purchase it under a perpetual or annual license, with discounts for academic institutions. For individuals not associated with government agencies, private companies or other organizations, there is a less expensive home license for personal use. Students can purchase a student license for a version designed for coursework and academic research. Early-stage technology startups can apply for startup-friendly pricing and opportunities.
Ezoic
Ezoic is an analytics-based advertisement testing and web optimization platform. It utilizes the concepts of big data and machine learning to learn how users engage with content and how to improve revenue. With deep revenue breakdowns, ad and layout testing, Google AMP converting and speed acceleration, it has several avenues for optimizing a site’s web presence and value. It links with more than 10,000 advertisement networks and is a partner with Google to maximize advertising options.
SAP HANA
SAP HANA is the in-memory database for SAP’s Business Technology platform with strong data processing and analytics capabilities that reduce data redundancy and data footprint, while optimizing hardware and IT operational needs to support business in real time. Available on-premise, in the cloud and as a hybrid solution, it performs advanced analytics on live transactional data to display actionable information. With an in-memory architecture and lean data model that helps businesses access data at the speed of thought, it serves as a single source of all relevant data. It integrates with a multitude of systems and databases, including geo-spatial mapping tools, to give businesses the insights to make KPI-focused decisions.
Panoply
Panoply is a fully-integrated data management platform that syncs, stores, organizes and analyzes data from many sources. It enables the use of search query language to explore data, then analyze and visualize it through its robust integration capabilities. Accessible anywhere via the cloud, it combines data warehousing, AI-powered data processing and a variety of integrations to provide a user-friendly data analysis infrastructure.
GoodData
GoodData is a powerful, embeddable, customizable SaaS solution that combines, analyzes and visualizes the internal and external data of an organization to help businesses change the way they make decisions, with a focus on data-driven best practices. It lets users process data, analyze trends and create visualizations that present information in an easily-digestible format. Users can interpret these visualizations to draw insights and make intelligent business decisions.
RapidMiner
The RapidMiner platform is a cloud-based series of data intelligence offerings, capable of all layers of a big data ecosystem. It can work with structured and unstructured data alike, preparing, blending, analyzing and visualizing it. It utilizes a code-free interface for designing big data workflows and integrations, capable of the complete data science life cycle. It can achieve top-level analytics like machine learning and predictive modeling. Its cloud deployment comes in managed or on-demand options. It has open-source and commercial versions.
Spark
Apache Spark is an open source unified analytics software for distributed, rapid processing. It distributes data across clusters in real time to produce market-leading speeds. It is rising in popularity in the space, catching up to its sister-offering, Hadoop, because of its quicker speeds and specific focus on optimizing processing performance and ability to stream data. It supports several coding languages, including Python, R, Scala, SQL and Java. It can function stand-alone, or be integrated into broader workflows easily.
Hortonworks
Hortonworks Data Platform is an open-source data analysis and collection product from Hortonworks. It is designed to meet the needs of small, medium and large enterprises that are trying to take advantage of big data. The company was acquired by Cloudera in 2019 for $5.2 billion. HDP has a number of features that help it process large enterprise-level volumes, including multi-workload processing, batch processing, real-time processing, governance and more.
Confluent
Confluent is a cloud-native data streaming platform for data storage and management. It integrates Apache Kafka with other systems and offers pre-built connectors for other sources. Users can get the most out of Kafka with real-time data flows and processing. Enterprise-grade security protects data, and automated monitoring detects potential problems. Processing is continuous, so data moves in real time and reaches the users who need it. Pipelines can be built and managed in a simple graphical interface with multiple programming languages supported.
MicroStrategy
MicroStrategy is a data analytics platform that delivers actionable intelligence to organizations of all sizes. It allows users to customize data visualizations and build personalized real-time dashboards. It leverages data connectivity, machine learning and mobile access to offer users comprehensive control over their insights. Due to its ease of use and scalability, it stands out as a leader in the enterprise analytics field. Users can choose between cloud, on-premise or hybrid deployment according to their needs.
QlikView
QlikView is a data discovery and customer insight platform from Qlik, a leader in the insight and intelligence space. However, it is not available for purchase any longer. Qlik Sense, Qlik’s next-generation offering, is available for new customers. It offers self-service data that can help drive decisions and generate significant ROI for technical skill level users. It’s built from the ground up to be affordable, scalable and adaptable. It can ingest data from diverse sources like big data streams, file-based data, and on-premise or cloud data. It is well-known for its data associations and relationship functionality, keeping data in context automatically. It delivers results quickly via its patented in-memory data processing module, processing data down to as little as 10% of its original size.
Talend
Talend is an open-source data integration and management platform that enables big data ingestion, transformation and mapping at the enterprise level. The vendor provides cross-network connectivity, data quality and master data management in a single, unified hub – the Data Fabric. Based on industry standards like Eclipse, Java and SQL, it helps businesses create reusable pipelines – build once and use anywhere, with no proprietary lock-in.The open-source version is free, with the cloud data integration module available for a monthly and annual fee. The price of Data Fabric is available on request.
Infor Birst
Infor Birst is a cloud-based analytics software tool that aims to help users discover insights without the need for analyst input. It unifies IT-managed enterprise data with user-owned data, supporting the blending of both in a top-down and bottom-up manner. It uses consistent business metrics to structure raw data into organized sets and visualizations. It helps users identify patterns and better understand their organization’s KPIs. It offers a seamless, integrated UI that allows users to perform every step of the data analysis process in a single interface, enabling a smooth experience. It can be deployed either from the cloud or self-hosted on-premise. Users can purchase it in three available formats: per-user fee, by department or business unit or by end-customer in embedded scenarios.
KNIME
KNIME is an open-source end-to-end data analytics solution. It utilizes visual workflows with drag-and-drop functionality and thousands of nodes to lessen the data analytics learning curve data, with more than 1,800 prebuilt default workflows for streamlined setup. It allows for data ingestion, preparing, cleansing, analyzing and visualizing. It can be scaled for deeper analytics through integrations with sophisticated data modeling capabilities. It can be hosted on-premise or in the cloud through Microsoft Azure.
Airflow
Airflow is an open-source Python framework that allows authoring, scheduling and monitoring of complex data sourcing tasks for big data pipelines. Aligned with the DevOps mantra of “Configuration as Code,” it allows developers to orchestrate workflows and programmatically handle execution dependencies such as job retries and alerting. Through the use of Directed Acyclic Graphs (DAGs), developers can customize pipeline processes as needed by using multi-step workflows. They can run part of the workflow at any time, even when tasks are being updated in real time. Besides out-of-the-box integrations with MySQL, Microsoft Server and SaaS platforms, it also provides custom connections to plugins. Robust and flexible, it is free to download for all users.
Vertica
Vertica is an analytics and data exploration platform designed to ingest massive quantities of data, parse it, and then return business insights as reports and interactive graphics. Elastically scalable, it provides batch as well as streaming analytics with massively parallel processing, ANSI-compliant SQL querying and ACID transactions. Deployable in the cloud, on-premise, on Apache Hadoop and as a hybrid model, its resource manager enables concurrent job runs with reduced CPU and memory usage and data compression for storage optimization. A serverless setup and advanced data trawling techniques help users store and access their data with ease.
Qlik Sense
Qlik Sense is a self-service data analytics software that enhances human intuition with the power of artificial intelligence to enable better data-driven business decisions. It allows organizations to explore their data and create intuitive and compelling visualizations from data insights with drag-and-drop simplicity. As the next-generation advancement of QlikView, released in 2014, it expands analytical possibilities to support the entire insights life cycle and helps businesses modernize their approach to intelligence. It has two editions: Business and Enterprise, offered on a per account annual subscription. Enterprises can choose between a hosted SaaS public cloud or multi-cloud, on-premise or private cloud deployment. Qlik Sense Business comes with a free 30-day trial. Its desktop version is available for free for personal use.
IBM Watson Analytics
IBM Watson is an AI-augmented data science solution that enables employees to harness the power of proprietary data, unlock its potential and apply insights gained from it in new ways. It offers a wide variety of customizable modules for lifecycle management, data applications, APIs and industry-focused specializations.
Qubole
Qubole is a cloud-based data lake management solution that enables fast data lake adoption for businesses. It allows continuous collaboration by ingesting and processing continuously generated data. Connect to a variety of structured and unstructured data sources and perform ad hoc and streaming analytics, build and test machine learning models and explore data.Explore, build, orchestrate and deliver data pipelines with ease while minimizing cost and maximizing performance. Users can choose a data format best suited to their workflow. It includes a centralized workspace, development tools, an inbuilt notebook environment and extensive integrations to provide end-to-end service with near-zero maintenance.
Azure Databricks
Azure Databricks is a unified big data analytics platform that provides data management, machine learning and data science to businesses through integration with Apache Spark. Integrating with a host of data sources, it pulls data from a wide variety of sources, transforms and then analyzes it through visualizations. In addition to setting up ETL flows, it empowers enterprises to create data models for predictive analysis, forecasting and future planning. The vendor offers three workloads based on the stages of analytics workflows — Jobs Compute and Jobs Light Compute for data engineers, and the All-Purpose Compute workload for data scientists.
Ayasdi
Owned by the SymphonyAI Group since 2019, Ayasdi is a machine intelligence platform that leverages statistical calculations and mathematical algorithms to deliver analytics to enterprises. It helps businesses connect the dots by segmenting complex, related datasets into groups through topological data analysis (TDA). Organizations can detect financial risk areas and fraud through automated machine learning workflows, and uncover previously undiscovered patterns and risks.Its sequential data processing and augmented analytics inclusions enable healthcare providers to create consistent patient care strategies. Running on Linux and Hadoop, it can be deployed on premises or in the cloud as a Software-as-a-Service (SaaS).
Actian
Actian is a cloud data management platform that enables data integration with fully managed warehousing, transformation and analytics for enterprises. It integrates with various cloud-based and on-premise technologies and services. With massively parallel processing and data compression on the back end, its embedded analytical engine works in tandem with a robust RDBMS, complementing its computing with built-in user-defined functions to process online transactions at scale.Part of the Cloud Security Alliance, the vendor consistently updates their best practices to ensure the security of its cloud services. It offers a 30-day free trial. Pricing is available on request.
1010data
1010data is a market intelligence and enterprise analytics solution that helps track consumer insights and market trends. In addition to vendor-critical insights, it provides brand performance metrics to buy-side entities. Seamlessly embeddable, it can also function as a standalone private-label option. Data scientists and statisticians leverage its integration with R to view and query data tables.It enables analytics development through its QuickApps framework. By tracking consumer spending trends and brand performance, it enables businesses to better position their products in the marketplace.
Pentaho Data Integration
Pentaho Data Integration helps organizations access, prepare and analyze all of their data from one place. It connects quickly and easily to any data source, whether it's structured or unstructured. It uses an extract, transform and load (ETL) approach to data management.Organizations can govern their data, ensure data quality and accelerate time to insight. Available on-premise and in the cloud, it’s easy to use and offers a wide range of features.
Apache Arrow
Apache Arrow is an open-source software development framework for building high-performing data analytics applications that process large, complex data sets. With an in-memory columnar format for data storage, it provides a query execution language that helps define the framework for analytics libraries. Language-agnostic due to easy translation, it acts as an interface between a wide range of programming languages and technologies.With a modern CPU architecture based on the single instruction, multiple data (SIMD) taxonomy, it processes data at lightning speeds. Its zero-copy design makes moving data round faster and more efficient.
Essbase
Oracle Essbase is an Online Analytical Processing provider for businesses to develop complex models of their activities that result in actionable insight. It can scale from simple ad-hoc queries to extensive, repeated multidimensional aggregations and present the results in a usable form. Through both retrospective and predictive analysis, business owners can maximize efficiency and profitability by turning data sources throughout the enterprise into usable information. It is configurable to an organization’s ongoing data needs.
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