Overview of Big Data:
Over the past few years, you must have heard the term “Big Data” which is defined in different ways.
Big Data describes the large volume of data in a structured and unstructured manner. The data belongs to a different organization and each organization uses such data for different purposes. So a large amount of data is not critical, the rather critical part is how organizations are using this data.
Big Data is a data set that is huge and complex so that traditional data processing applications are inadequate to deal with them. There are challenges to managing such a huge volume of data such as capture, store, data analysis, data transfer, data sharing, etc. Big Data follows the 3V model as “High Volume”, “High Velocity” and “High Variety”.
The importance of Big Data is not about how much volume of data is present rather it is focused on what you do with that data.
In today’s world, by collecting data you can find answers for – root cause for failure, recalculating the risk profiles, etc. It also helps to reduce cost, faster decision making. Hadoop technology and cloud-based analytics help business analyze the information or data immediately so decision making is much faster.
What You Will Learn:
Top Big Data Companies to Look For
- InData Labs
- HP Enterprise
Let’s see a few details about these companies.
iTechArt has been the partner of choice for fast-growing startups and innovative companies since 2002, providing fully dedicated engineering teams and custom software solutions. Headquartered in New York, the company has over 200 active clients worldwide, with 90 percent operating on the frontier of emerging technologies and markets.
Their forte is agile dedicated teams of engineers who leverage time-tested big data development services to help clients manage data more effectively and efficiently.
Their Big Data Expertise:
- Artificial neural networks
- AI algorithms and applications
- Natural language processing (NLP)
- IoT solution development
- Big data cluster management
- Parallel computing
- GPU processing
- Data governance
- Real-time/Batch processing
#2) InData Labs
InData Labs is a top Big Data and AI technology company. Since 2014, the company has been developing AI-powered solutions and has a proven track record of projects for various industries. InData Labs specializes in AI-powered software development, Big Data, and data science project consulting and development.
Big Data Transformation Services include:
- Architecture Analysis: Understanding of business needs based on which proposing plans for improvements and automation.
- Big Data Pipelines: Preparing data and building event-based infrastructure when data requires immediate processing.
- Architecture Improvement: Implementing best practices and automation processes into the existing infrastructure.
- Data Analysis and Visualization: Preparing and visualizing reports customized for specific clients’ needs.
Use cases InData Labs works on (not exhaustive):
- Predictive maintenance or condition monitoring
- Warranty reserve estimation
- Propensity to buy
- Demand forecasting
- Process optimization
- Predictive inventory planning
- Recommendation engines
- Upsell and cross channel marketing
- Market segmentation and targeting
- Customer ROI and lifetime value
Healthcare and Life Sciences
- Alerts and diagnostics from real-time patient data.
- Disease identification and risk satisfaction.
- Patient triage optimization
- Proactive health management
- Healthcare provider sentiment analysis.
- Risk analytics and regulation
- Customer segmentation
- Cross-selling and up-selling
- Sales and Marketing Campaign Management
- Credit worthiness evaluation
Energy, Feedstock, and Utilities
- Power usage analytics
- Seismic data processing
- Carbon emissions and trading
- Customer-specific pricing
- Smart grid management
- Energy demand and supply after musician
Travel and Hospitality
- Aircraft scheduling
- Dynamic pricing
- Social media – Consumer Feedback and Interaction Analysis
- Customer complaint resolution
- Traffic patterns and congestion management
ScienceSoft is a US-headquartered provider of big data solutions and services with 32+ years of experience in data analytics and data science.
ScienceSoft’s expertise covers a comprehensive list of big data technologies, including:
- Apache Hadoop ecosystem (Hadoop Common, Hadoop Distributed File System, Hadoop YARN, Hadoop MapReduce, Hadoop Ozone)
- Apache Spark
- Apache Hive
- Apache Cassandra
- Amazon big data ecosystem (Amazon EMR, Amazon S3, Amazon DynamoDB, Amazon Kinesis, Amazon Redshift, etc.)
- Microsoft Azure big data ecosystem (Azure Data Lake Storage, Azure Cosmos DB, Azure Stream Analytics, Azure Synapse Analytics, etc.), and more.
ScienceSoft helps organizations store and manage big data cost-effectively, as well as derive actionable insights out of big data by enabling:
- Operational analytics
- Customer (behavior) analytics
- Risk management and fraud detection
- Asset tracking and monitoring
- Predictive maintenance
- Supply chain optimization
- Personalization (personalized marketing, personalized care plan recommendations, etc.)
- Remote staff/patient monitoring, etc.
Being ISO 9001 and ISO 27001 certified, ScienceSoft delivers big data solutions relying on a mature quality management system and applying security protocols to eliminate any risk to customers’ data security.
ScienceSoft’s big data service offering includes:
Big Data Consulting
- Big data solution implementation/evolution strategies and roadmaps.
- Big data solution architecture.
- Big data tech selection.
- Big data quality management.
- User adoption strategy, etc.
Big Data Implementation
- Big data solution implementation strategy.
- Big data solution architecture design.
- Big data solution development (a data lake, DWH, ETL/ELT setup, big data analysis, big data reporting, and dashboarding).
- Big data governance setup (big data quality, security, etc.).
- Predictive modeling with ML training and setup.
Big Data Solution Support
- Big data solution administration (software updates and reconfiguration, adding new users, etc.).
- Big data governance (big data cleaning, security, backup, and recovery).
- Big data solution health checks.
- Big data solution performance monitoring and troubleshooting.
Big Data Managed Analytics Services
- Getting your big data collected, processed, and presented in the form of predefined and ad hoc reports for a subscription fee.
Xplenty is a cloud-based data integration, ETL, and ELT platform that will streamline data processing. It can bring all your data sources together. It will let you create simple, visualized data pipelines to your data lake.
Xplenty’s Big Data processing cloud service will provide immediate results to your business like designing data flows and scheduling jobs. It can process structured and unstructured data.
Through this platform, organizations will be able to integrate, process, and prepare data for analysis on the cloud. Xplenty will ensure that businesses can quickly and easily benefit from big data opportunities without investing in hardware, software, or related personnel.
Every organization will be able to immediately connect to a variety of data stores. Companies will get a rich set of out-of-the-box data transformation components with Xplenty.
Xplenty has a team of top data experts, engineers, and DevOps. This team provides a data integration platform with a simplified data processing service. Xplenty has solutions for Marketing, sales, support, and developers.
International Business Machine (IBM) is an American company headquartered in New York. IBM is listed at # 43 in Forbes list with a Market Capitalization of $162.4 billion as of May 2017. The company’s operation is spread across 170 countries and the largest employer with around 414,400 employees.
IBM has a sale of around $79.9 billion and a profit of $11.9 billion. In 2017, IBM holds most patents generated by the business for 24 consecutive years.
IBM is the biggest vendor for Big Data-related products and services. IBM Big Data solutions provide features such as store data, manage data and analyze data.
There are numerous sources from where this data comes and accessible to all users, Business Analysts, Data Scientist, etc. DB2, Informix, and InfoSphere are popular database platforms by IBM which supports Big Data Analytics. There are also famous analytics applications by IBM such as Cognos and SPSS.
IBM’s Big Data Solutions are as below:
#1) Hadoop System: It is a storage platform that stores structured and unstructured data. It is designed to process a large volume of data to gain business insights.
#2) Stream Computing: Stream Computing enables organizations to perform in-motion analytics including the Internet of Things, real-time data processing, and analytics
#3) Federated discovery and Navigation: Federated discovery and navigation software help organizations to analyze and access information across the enterprise. IBM provides below listed Big Data products which will help to capture, analyze, and manage any structured and unstructured data.
#4) IBM® BigInsights™ for Apache™ Hadoop®: It enables organizations to analyze a huge volume of data quickly and in a simple manner.
#5) IBM BigInsights on Cloud: It provides Hadoop as a service through the IBM SoftLayer cloud infrastructure.
#6) IBM Streams: For critical Internet of Things applications, it helps organizations to capture and analyze data in motion.
Visit official site: IBM
#6) HP Enterprise
HP Enterprise was acquired by Micro Focus including Vertica
Micro Focus has built up a strong portfolio in Big Data products in a very short time span. The Vertica Analytics Platform is designed to manage a large volume of structured data and it has the fastest query performance on Hadoop and SQL Analytics. Vertica delivers 10-50x faster performance or more compared to legacy systems.
With the help of Big Data software, it enables different organizations to store, analyze and explore data irrespective of the source of data, type of data or location of data.
Featured Big Data Software, Solutions and Services list is as given below:
#1) Vertica Data Analytics
Vertica combines the power of a high-performance, massively parallel processing SQL query engine with advanced analytics and machine learning so you can unlock the true potential of your data with no limits and no compromises.
It can deploy anywhere across multiple clouds, commodity hardware, on any Hadoop distribution system. It is integrated with open-source, eco-friendly architecture.
It provides a single environment for structured, semi-structured and unstructured data. It has rich media intelligence, visualization, and exploration. Using the IDOL Natural Language Question Answering power, different organizations are tapping the potential of Big Data by breaking the barriers between machines and humans.
Visit official site: Micro Focus
Teradata is founded in 1974 with headquarter at Dayton, Ohio. Teradata has more than 10K employees across 43 countries and around 1,400 customers with a Market Capitalization of $7.7B. It has extensive 35+ years of experience in innovation and leadership. Teradata Corp. provides an analytic data platform, marketing, consulting services, and analytics application.
Teradata helps different companies to get value from their data. Teradata’s Big Data Analytical solutions and a team of experts help different organizations to gain the advantage of data. Teradata portfolio includes various Big Data applications such as Teradata QueryGrid, Teradata Listener, Teradata Unity, and Teradata Viewpoint.
Teradata has the following products:
#1) Integrated Data Warehouse
- It is the world’s most powerful database and enterprise-class which gives the most value from your data
- It has a 360 view of your business
- It has the ability to integrated data from multiple sources
- It is an open-source and enterprise-ready software
- It leverages reusable templates to increase the productivity
#3) Aster Big Analytics Appliance
- It helps in generating business insights fast and easily. Along with that, it helps in meeting all business needs
- Quick deploy, easy to manage and highest ROI
#4) Data Mart Appliance
- Leverage the analytical power of the Teradata database
- Versatile and cost-effective
- Simplified platform and high-performance architecture
Visit official site: Teradata
Oracle offers fully integrated cloud applications, platform services with more than 420,000 customers and 136,000 employees across 145 countries. It has a Market capitalization of $182.2 billion and sales of $37.4 B as per Forbes list.
Oracle is the biggest player in the Big Data area, it is also well known for its flagship database. Oracle leverages the benefits of big data in the cloud. It helps organizations to define its data strategy and approach which includes big data and cloud technology.
It provides a business solution that leverages Big Data Analytics, applications, and infrastructure to provide insight for logistics, fraud, etc. Oracle also provides Industry solutions which ensure that your organization takes advantage of Big Data opportunities.
Oracle’s Big Data industry solutions address the growing demand for different industries such as Banking, Health Care, Communications, Public Sector, Retail, etc. There are a variety of Technology solutions such as Cloud Computing, Application Development, and System Integration.
Oracle offers different products as below:
- Oracle Big Data Preparation Cloud Services
- Oracle Big Data Appliance
- Oracle Big Data Discovery Cloud Services
- Data Visualization Cloud Service
Visit official site: Oracle
SAP is the largest business software company founded in 1972 with headquarters in Walldrof, Germany. It has a Market Capitalization of $119.7 billion with total employee count as 84,183 as of May 2017.
As per the Forbes list, SAP has sales of $24.4 billion and a profit of around $4 B with 345,000 customers. It is the largest provider of enterprise application software and the best cloud company with 110 million cloud subscribers.
The SAP provides a variety of Analytics Tool but its main Big Data Tool is the HANA-in memory relational database. This tool integrates with Hadoop and can run on 80 terabytes of data.
SAP helps the organization to turn a huge amount of Big Data into real-time insight with Hadoop. It enables distributed data storage and advanced computation capabilities.
SAP Big Data provides the following listed products:
#1) SAP Predictive Analytics
- It uses a predictive algorithm and machine learning to anticipate the future outcome and guide the business in the right direction
- Using this technique thousands of predictive models can be created, deployed and maintained
- It automates data preparation, deployment of predictive modeling
#2) SAP IQ
- Formerly it is known as Sybase IQ. It transforms business and enhances the decision making with SAP IQ
- It is an extremely scalable and robust security
#3) SAP BusinessObjects BI
- It analyzes a high volume of data with greater performance
- It proactively grabs the new business opportunity and responds to potential threats
Visit official site: SAP
DELL EMC helps businesses to store, analyze and protect their data. It provides an infrastructure to get the business outcome from Big Data. It helps the organization to understand customer behavior, risk, operations. Dell EMC has over 50% growth with Data Analytics.
Data stored in one centralized repository which simplifies the analytics and management. Powerful infrastructure gives your organization a competitive edge and increased revenue. SAP Big Data Foundation has below listed products:
- PowerEdge for Hadoop
Visit official site: EMC
Amazon.com founded in 1994 with headquarters in Washington. As of May 2017, it has a Market Capitalization of $427 billion and sales of $135.99 billion as per Forbes list. The total employee headcount as of May 2017 is 341,400.
Amazon is well known for its cloud-based platform. It also offers Big Data products and its main product is Hadoop-based Elastic MapReduce. DynamoDB Big Data database, the redshift, and NoSQL are data warehouses and are work with Amazon Web Services.
Big Data Analytics application can be built and deploy quickly using Amazon Web Services. These applications can be built virtually using AWS which provides fast and easy access to low cost IT resources. AWS helps to collect, analyze, store process, and visualize big data on the cloud.
Below is given a list of Analytics framework:
- Amazon EMR
- Amazon Elasticsearch Service
- Amazon Athena
The list given below is the real-time Big Data Analytics:
- Amazon Kinesis Firehose
- Amazon Kinesis Streams
- Amazon Kinesis Analytics
Amazon also provides Business Intelligence, Artificial Intelligence Internet of Things, Data Movement etc.
Visit official site: Amazon
It is US-based Software and Programming Company, founded in 1975 with headquarters in Washington. As per Forbes list, it has a Market Capitalization of $507.5 billion and $85.27 billion of sales. It currently employed around 114,000 employees across the globe.
Microsoft’s Big Data strategy is wide and growing fast. This strategy includes a partnership with Hortonworks which is a Big Data startup. This partnership provides HDInsight tool for analyzing structured and unstructured data on Hortonworks data platform (HDP)
Recently Microsoft has acquired Revolution Analytics which is a Big Data Analytics platform written in “R” programming language. This language used for building Big Data apps that do not require a skill of Data Scientist.
Microsoft and Hortonworks have three solutions based on HDP:
#1) HDInsight: It is cloud-hosted service and uses Azure cluster to run on HDP. It can be integrated with Azure storage
#2) HDP for Windows: It is a configurable Big Data cluster that can be installed on the Windows server. It can also be installed on a virtual machine or physical hardware in the cloud
#3) Microsoft Analytics Platform System: It allows data in Hadoop to be queried and can be combined with relational data. Such data can be moved in or out of Hadoop
Visit official site: Microsoft
Google is founded in 1998 and California is headquartered. It has $101.8 billion market capitalization and $80.5 billion of sales as of May 2017. Around 61,000 employees are currently working with Google across the globe.
Google provides integrated and end to end Big Data solutions based on innovation at Google and help the different organization to capture, process, analyze and transfer a data in a single platform. Google is expanding its Big Data Analytics; BigQuery is a cloud-based analytics platform that analyzes a huge set of data quickly.
BigQuery is a serverless, fully managed and low-cost enterprise data warehouse. So it does not require a database administrator as well as there is no infrastructure to manage. BigQuery can scan terabytes data in seconds and pentabytes data in minutes.
Google provides below listed Big Data Solutions:
#1) Cloud DataFlow: It is a unified programming model and helps in data processing patterns which include ETL, batch computation, streaming analytics.
#2) Cloud Dataproc: Google’s Cloud Dataproc is a managed Hadoop and Spark service which easily processes big data sets using open source tool in the Apache big data ecosystem.
#3) Cloud Datalab: It is an interactive notebook that analyzes and visualizes data. It is also integrated with BigQuery and enables to access to key data processing services.
Visit official site: Google
VMware founded in 1998 and headquartered is in Palo Alto, California. Around 20,000 employees are working and it has a Market Capitalization of $37.8 billion as of May 2017. Also as per Forbes data, it has sales of around $7.09 billion.
VMware is well known for its cloud and virtualization but nowadays it is becoming a big player in Big Data. Virtualization of Big Data enables simpler Big Data infrastructure management, delivers results quickly and very cost-effective. VMware Big Data is simple, flexible, cost-effective, agile and secure.
It has a product VMware vSphere Big Data Extension which enables us to deploy, manage and controls Hadoop deployments. It supports Hadoop distributions which include Apache, Hortonworks, MapR, etc. With the help of this extension, the resource can be used efficiently on the new and existing hardware.
Visit official site: VMware
Splunk Enterprise started as a log analysis tool and expanded its focus on machine data analytics. With the help of machine data analytics, the data or information is usable by anyone.
It helps in monitoring the online end to end transactions; monitor the security threats if any, helps to study customer behavior and helps for sentiment analysis on the social platform. Using the Splunk Big Data you can search, explore and visualize data in one place.
Splunk’s Big Data solutions include:
- Splunk Analytics for Hadoop
- Splunk ODBC Driver
- Splunk DB Connect
Visit official site: Splunk
Alteryx software is for the business user and not for a data scientist. Alteryx provides the ability for analysts to meet their organization’s analytics needs. Alteryx delivers a platform for self-service data analytics. It has access and ability to integrate from Big Data environment such as Hadoop SAP Hana, Microsoft SQL Azure Database, etc.
Prepare and blend data inside and outside the Big Data environment.
Big Data analytics provides an opportunity for the organization to get new sources of insights from a new source of data. Alteryx allows different organizations to take advantage of data from a big data environment. This data again can be integrated with external datasets to gain the maximum value from corresponding data sources
Visit official site: Alteryx
Cogito uses a famous technology as – behavioral analytics technology. Cogito analyzes the voice signals in phone calls to improve communication, customer emails, social media behavior, etc.
Cogito also detects human signals and provides guidance to improve the interaction quality with everyone. It helps in phone support and helps organizations to manage the agent performance. Real-time guidance increases the call efficiency and gets the customer feedback, perception after every call.
Visit official site: Cogito
Clairvoyant is a leading multinational data science and engineering firm, builds high-quality data solutions for various enterprises across several domains.
Backed by the firm’s vast technical expertise, these solutions are well-known for their precision, agility, scalability, and ease of use. These solutions continue to help companies rapidly analyze huge volumes of data efficiently.
The company specializes in the end-to-end development and operationalization of Artificial Intelligence(AI) and Machine Learning(ML) solutions for organizations that function on tremendous volumes of data and need efficient decision-making capabilities.
These solutions have helped derive actionable insights and business decisions for an array of satisfied clients. It also has a competent Managed Services team that has efficiently managed 300+ large-scale Big Data infrastructures.
It spares clients from the time, effort, and cost consumed in building a skilled data management team that can keep an eye on all forms of data ingestion and insight generation processes.
Clairvoyant’s adept Managed services team undertakes all the heavy-lifting, right from setting up and managing the day-to-day operations to enable clients architect complex big data projects effortlessly from the ground up.
Headquartered in Phoenix, Arizona, the company serves multiple Fortune 500 clients with its superior services in the fields of big data, data analytics, cloud, Artificial Intelligence, Machine Learning, and other disruptive technologies.
With an employee base of more than 300, Clairvoyant has its locations in more than 10 cities and 3 countries. Its offerings are consumed by several organizations belonging to more than 10 sectors.
In this article, we have seen the top Big Data Companies. This is not an exhaustive list and there are many other companies who are startup now but have the capabilities to grow faster. This will be challenging for the other rival companies.
There are different products, solutions provided by these companies and are used by other organizations as per their need. Now it’s your turn to add more companies to the above list!