- Only 18% of companies believe they have the skills necessary to gather and use insights effectively.
- Only 19% of companies are confident that their insights-gathering processes contribute directly to sales effectiveness. (source: McKinsey)
Simply collecting data does not unleash its business effectiveness. Big data is a term for large volumes of data – both structured and unstructured – that inundates a business on a day-to-day basis. But it’s not the amount of data that’s important. It’s what organizations do with the data that matters.
Here are the 15 best Big Data Companies and why they stand out according to sources that rank them highly.
Best Big Data companies with the biggest revenue
Founded in 20014, Palantir builds software that connects data, technologies, humans and environments. Big Data revenues topped $418 million — with a 50-50 split between software and services. Key customers include the S.E.C., which hired Palantir to help the government analyze data to find terrorists, and to help it uncover illegal trading activity. What does Palantir’s software do? It lets non-technical users visualize reams of data from several databases in a user-friendly way. That way, they can look at specific bits of information and the links among them, so they can find answers to complex questions and find the proverbial needle in a haystack. (Source:Information Management)
PriceWaterhouseCoopers generated $312 million from Big Data revenues in 2013. All of that revenue involved consulting services. The opportunities should continue to be strong, considering 41% of PWC’s customers are concerned about Big Data overload. PWC is one of the leading companies in the world offering advisory services for financial entities with complex, computerized systems, and massive amounts of data. (Source: Information Management)
IBM has momentum in the Big Data market — generating $1.37 billion in revenues. Those revenues were split across hardware (31%), software (27%) and services (42%). Eager to potentially accelerate those Big Data revenues, IBM expanded cloud-focused releases of Cognos while also working more closely with Watson-focused software. IBM has a big Big Data play through which it is aiming to be relevant to all market sectors. The company released 20 industry solutions as it targets, getting its analytics embedded into all areas of the maturing Big Data market. (Source:Information Management)
Most well funded Big Data startups
Domo isn’t just another business management tool. Rather, we understand that Domo is an intelligent dashboard that displays and analyzes various key business metrics in real-time. Its ability to not only aggregate information that’s typically scattered across different sources (like spreadsheets, social media, or databases) into a single dashboard, but to then also continuously refresh the results, is a transformation for those involved in business operations. Domo also announced that it received $200 million in Series D funding this past April. Domo’s been around since 2010, but that’s still an absurdly large amount of funding for a company that’s just publicly entered the market. (Source: Tech.co)
Roundforest was named one of 16 Israeli Startups Ready To Take On 2016. Roundforest is a data-driven e-commerce startup that optimizes every step of the consumer’s purchase path. They’ve developed a proprietary automated engine that removes the guesswork out of performance optimization. Its founders previously worked at Google and Intel and are determined to apply their background in machine learning and data analysis to help consumers make better shopping decisions, especially since Roundforest is already reaching more than 10 million users a month. (Source: Tech.co)
It’s safe to say that 2015 was SQream’s best year yet. This past year, SQream won five major awards (Red Herring Global 100, Red Herring Asia 100, Best in Biz, Stevie, and Tech Trailblazers Regional), launched its second product (GenomeStack), and raised $7.4 million in Series B funding. In 2010, SQream Technologies introduced its GPU-based technology that, through massive parallel computing, boosts analytics performance up to 100x faster than its competitors—meaning Teradata, IBM Netezza, Oracle Exadata, and Amazon Redshift on the Cloud really ought to watch out. SQream is boldly taking on the Goliaths. (source: Tech.co)
Most recommended Big Data Companies by employees to friends
Quaero’s data management platform (QDMP) and its AdVantage platform are built upon Cloudera’s Distribution of Hadoop (Cloudera Enterprise). The AdVantage platform is targeted for clients in the media industry to better understand their audience, enhance engagement, create richer experiences, and increase overall audience value. Quaero has deployed the platform across several clients in the media industry (ranging in ingestion volume from ~3MM to ~1.5 Billion records per day). Cloudera Enterprise offers the right mix of components to build a robust data platform which supports both reporting and analytics which can deal with all sorts of data. (Source: DeZyre)
InsightSquared is a sales performance analytics company for fast-growing tech businesses. Unlike spreadsheets, InsightSquared’s visual, maintenance-free reports and dashboards provide a custom lens into real-time sales results. InsightSquared offers robust, powerful data intelligence in a system that is accessible and affordable. InsightSquared is entirely web-based, so setup is quick, painless, and doesn’t require dedicated IT personnel. Pricing is monthly, eliminating costly up-front fees. Features include activity tracking, employee scorecards, sales forecasting, ratios and KPIs, data quality monitoring, and more. With InsightSquared, users have access to dashboards and interactive visualizations that take static data and create charts with dynamic drill-down capabilities, configured to track just about any kind of data critical to business operations. (Source: InsightSquared)
Trifacta enables organizations to use data to drive innovation by providing a more productive and accessible method of exploring and experimenting with data of all shapes and sizes. Data wrangling — formatting and cleaning — is a sore spot and stumbling block for many, but you often can’t do much visualization- or analysis-wise until the data is in order. My projects folder is filled with one-off Python scripts written for specific datasets (and steps within steps). Trifacta Wrangler aims to streamline the process with a click interface and automation. The desktop software is free to use and available for PC and Mac. (Source: DeZyre)
Coolest Big Data Start Ups
An increasing number of businesses are implementing Hadoop systems, using them to collect huge volumes of disparate data from multiple sources. But making use of that data isn’t so easy — most traditional business analytics tools can’t directly access Hadoop data, and IT departments have to step in to prepare the data or move it to another system to make it available for everyday business workers. Arcadia Data is developing visual analytics software that overcomes those hurdles by directly accessing data stored in Hadoop clusters. The technology uses Hadoop as an operating system, allowing it to run directly on Hadoop servers and access data stored in the Hadoop Distributed File System. (Source: CRN)
San Francisco-based DataHero is focused on developing “self-service” business analytics software. The DataHero cloud-based service collects data from such disparate sources as Box, Dropbox, Google Drive, Excel, Office 365, Marketo, HubSpot, and Eventbrite, and turns it into charts and dashboards. For the business analytics software industry, the challenge has been developing analytical applications that can be used by a broad range of everyday business users without a lot of assistance from the IT department. DataHero is among the few companies that’s close to achieving that. (Source: CRN)
Interana is another big data startup that’s developing technology to help businesses analyze streaming data in realtime. The company’s events-based analytical software works with clickstream data and other “events-based” information to help users answer questions about how customers behave and how products are used. The goal is to provide actionable business intelligence for nontechnical users. No longer do you have to have a department of people who are the high priests of data. Now, the person who needs the data–the person who wants the business answers from the data–can have direct access to it. (Source: Tech.co)
Best Big Data companies to watch
Cazena provides fast and inexpensive processing of big data in an encrypted cloud via what it calls enterprise Big Data-as-a-Service offerings broken down into Data Lake, Data Mart, and Sandbox editions. Cazena aims to greatly simplify big data processing for businesses. Ideally, it should only take three clicks to set up a data processing job with Cazena. The service strips away the complexities by trying to automatically figure out what technology to use to analyze a given set of data. It then automatically provisions, optimizes, and manages that workflow for its customers, no matter whether it’s a Hadoop, Spark, or MPP SQL (think Amazon Redshift) job. The company is led mainly by former movers and shakers at Netezza, a data warehouse company acquired by IBM in 2010 for $1.7 billion. (Source: Network World)
Experfy is a cloud-based consulting marketplace designed to match up big data and analytics experts with clients who need their services. Experfy provides advisory services, big data readiness assessments, road maps, predictive dashboards, algorithms, and a number of custom analytics solutions. Expert Panels consist of a closely curated group of Big Data leaders within different areas of specialization—from Marketing Analytics, Personalization and Security Analytics to Financial Services, Healthcare and Retail. In addition, Experfy’s proprietary data platform, tools, and processes support repeatable projects and use-cases in specific verticals. Experfy provides a self-service model for smaller companies and a high-touch concierge service with project management for larger enterprises. (Source: Forbes)
Tamr uses machine learning and human input to enable customers to make use of data currently silo-ed in disparate databases, spreadsheets, logs, and partner resources. Most companies have many dozens of Oracle instances, hundreds of databases, and many thousands of tables. There is [currently] no way to catalog and know what’s out there. Tamr can create a central catalogue of all these data sources (and spreadsheets and logs) spread out across the company and give greater visibility into what exactly a company has. Tamr’s tech got its start at MIT’s CSAIL. (Source:Network World)
Do these best Big Data companies help you see how to make data an asset at your company? Do you see why these Big Data companies stand out? Does your organization need guidance navigating Big Data?
