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Insights On Advanced Analytics Unlocking Opportunities

Though many businesses understand the importance of Big Data Analytics and its potential to impact business growth in the areas of marketing, finance and operations, not every organisation knows how to achieve these benefits. One key to unlocking value is harnessing the power of Advanced Analytics.

“Advanced Analytics is the autonomous or semi-autonomous examination of data or content using sophisticated techniques and tools, typically beyond those of traditional business intelligence (BI), to discover deeper insights, make predictions, or generate recommendations.” – Gartner.

Data mining, machine learning, predictive & prescriptive analytics, pattern matching, neural networks and location intelligence are just some of the categories that make up Advanced Analytics. Whilst the applications of Advanced Analytics are many, here are five ways it may help your business.

 

#1 – RISK MINIMISATION

All businesses have some level of risk, including possibilities of fraud, intellectual property theft and ransomware. Fortunately with advanced analytics, these risks can be measured, identified and acted upon.

“Advanced analytics capabilities enable clearer visibility into the challenges associated with managing the many types of risk in such key areas as operations, regulatory compliance, supply chain, finance, ecommerce and credit. By using analytics to measure, quantify and predict risk, leaders can rely less on intuition and create a consistent methodology steeped in data-driven insights.” – Deloitte.

 

#2 – INCREASING CUSTOMER LOYALTY

“With improved customer experience and service, and more efficient operations leading to increased customer acquisition and retention, companies are realising what advanced analytics can do for their operations. And as these data-driven strategies take hold, they will become an increasingly important point of competitive differentiation.” – Tribridge Connections.

Advanced analytics is changing the way we engage with customers. We are now able to use data to predict consumer buying behaviours that help with micro-targeting, up-selling and churn management.

 

#3 – EFFECTIVE PROMOTIONAL STRATEGIES

Ensuring that marketing efforts are effective requires an organisation to invest in promotional strategies that are based on data rather than theory. Today’s business environment requires data to support effectiveness claims and seeks marketing results that are not usually achieved without the sophistication that advanced analytics enables.

Predictive analytics based on machine learning technologies can help in this regard, as the various predictive models can be used for customer segmentation, analysing customer engagement, collaborative filtering, up-selling and prioritising leads.

“Predictive analytics appears to have the potential to double marketing success measures in customer engagement and targeted sales across B2B and B2C industries.” – Daniel Faggella: CEO & Founder of TechEmergence.

 

#4 – BETTER DECISION MAKING

Data-driven decision making derived from Advanced Analytics enables businesses to decrease costs, increase revenue and achieve regulatory compliance.

“Companies that make better decisions, make them faster and execute them more effectively than rivals nearly always turn in better financial performance. Not surprisingly, companies that employ advanced analytics to improve decision making and execution have the results to show for it.” – Bain & Company.

 

#5 – IMPROVING EFFICIENCY

“A Big Data and Analytics Implementation can help companies uncover ways to make operations more efficient and effective by improving asset efficiency and streamlining global operations.” – IBM.

Predictive analytics tools such as Optimotive, Infer and SAP Predictive Analytics allow businesses to optimise operations and be better prepared to respond to changes in the marketplace.

Companies that are actively analysing and using data are experiencing the rewarding benefits of staff and operational efficiency. For example, companies can now build forecasting models that accurately predict sales volumes, optimise preventative maintenance or perform optimal resource scheduling. These models are swiftly trained, self-optimise and can accommodate highly complex input considerations, or computations at great scale. This allows businesses to consider the use of data types they’d not previously have been able to harness, such as detailed data from customer website use or use of assets such as machines and vehicles.

 

 

To discuss Advanced Analytics and other topics, please contact the team at Contexti – +61 2 8294 2161 | connect@contexti.com

 

For more resources, please see below:

IT’s 9 Biggest Security Threats

Smarter Insights With Risk Analytics

5 Hottest Trends In Advanced Analytics

The Five Top Uses For Advanced Analytics

Creating Value Through Advanced Analytics

Advance Your Business With Advanced Analytics

Neural Designer | Advanced Analytics At Your Hands

Advanced Analytics Driving Better Business Decisions

What Are Neural Networks & Predictive Data Analytics

Improving Operational Efficiency With Big Data Analytics

Using Machine Learning To Improve Contact Centre Effectiveness

Predictive Analytics For Marketing – What’s Possible and How It Works

Stop Chasing Opportunities You Can’t Win. Using Advanced Analytics For Microsoft Dynamics

Big Data & Augmented Intelligence

“Each year computers are getting faster, but at the same time we as humans are getting better at using them.” – Daniel Gutierrez: Data Scientist at AMULET Analytics.

Augmented intelligence is the use of information technology to elevate human intelligence. It focuses on the assistive role of AI, highlighting the fact that it is designed to enhance human intelligence rather than replace it, by helping employees understand and keep up-to-date with the increasingly digital world that we live in.

Sean Gourley, CEO of Stealth Machine Intelligence Company, describes Augmented Intelligence as “humans and machines learning together to solve very, very difficult problems that neither one can solve by themselves.On the one side, you’ve got a very complex world, and we use mathematics to simplify it, and the other side, we’ve got the human version 1.0, where we use visualisation to enhance our natural cognitive ability, and It’s being used to solve some of the most difficult problems in the world.”

Companies like Quid, CognitiveScale, Eolian and Virtualitics are using Augmented Intelligence to improve their business outcomes, with many other emerging start-ups following the lead. Here are some examples of how the interface between humans and machines can help you increase the success of your organisation.

 

#1 – CONTEXTUAL DISCOVERY

Contextual discovery refers to the early phases of research where new knowledge or different ways of thinking about a subject are introduced. With the combined power of machine learning and human curation, contextual awareness across the entire data and analytics workflow is impacted.

“Augmented Intelligence enables contextual discovery so users can find what they’re looking for based on natural language queries and context of their work.” – Vice President of Brand Experience at Brainspace.

 

#2 – ENABLING OPPORTUNITIES ACROSS THE ORGANISATION

“Augmented Intelligence is the perfect marriage of machine learning and human intuition, enabling any user to become a data scientist; R&D can use it to research patents, HR can use it for workforce analytics, or corporate investigators can use it to explore cases.” – Brainspace.

Augmented Intelligence serves multiple purposes in an organisation across sales, finance, HR, operations and marketing departments, helping with the streamlining and classification of data, increasing savings, enabling better employee management and resource allocation whilst also reducing human error.

“Using augmented intelligence to make suggestions to staff, and to record their response, means that humans and the machines can work together to come up with the best solutions. There is less need to worry that people are going to miss important actions or take wrong decisions because of the visibility of what’s going on.” – Dataconomy.

 

#3 – FASTER & MORE ACCURATE INSIGHTS

“Quantitatively, the speed with which users can extract key insights with machine learning can save your organisation significant time and allocated costs. Augmenting worker intelligence allows your organisation to extract valuable data hidden in all corners of the company and connect it in ways that make sense to human users.” – Brainspace.

Time management is of high importance in every organisation. With augmented intelligence, the ability to extract meaning from unstructured data and present it logically enables the organisation to derive higher quality insights more quickly.

“AI developers are looking for opportunities to augment our abilities, and to develop tools to do tasks that we cannot do. Consider healthcare professionals, who only have seconds or minutes to make huge decisions.” – Ronald Van Loon: Director of Advertisement.

 

#4 – SECURITY ANALYSIS

Using AI, a business can analyse reams of structured and unstructured data and identify errors and security breaches faster than any human alone. Augmented Intelligence tools, like IBM Watson, are proving to be effective at this.
“Dozens of organisations are already working with this technology and helping discover new ways Watson can be used in the fight against cybercrime. In the future, bots will seek out network vulnerabilities, diagnose them, and recommend ways to patch them — all while working seamlessly with cybersecurity experts, who will be even more valuable in the fight against cybercrime because they have been trained in the use of augmented intelligence.” – Sandy Bird: Chief Technology Officer at IBM Security.

 

 

 

For more resources, please see below:

The Hype – And Hope – Of Artificial Intelligence

Augmented Intelligence: What You Should Know

How Augmented Intelligence Helps Businesses Grow

The Shift to Augmented Intelligence and How It Helps Your Organisation

Just Buying Into Modern BI And Analytics? Get Ready For Augmented Analytics

Big Data And The Rise of Augmented Intelligence: Sean Gourley at TEDx Auckland

Augmented Intelligence: How To Combine Human & Artificial Intelligence To Change Behaviour

Big Data & Analytics, Virtual & Augmented Reality, Artificial Intelligence & Cloud Are Driving Universities To Innovate

 

To discuss Augmented Intelligence and other topics, please contact the team at Contexti – + 61 28294 2161 | connect@contexti.com

Big Data Analytics – Enabling The Agile Workforce

In a fast-paced, constantly evolving digital era, time waits for no one. Agility, fast recovery from failure and adaptability to change continue to grow in importance for businesses who want to remain competitive. The capability to be this sort of business requires the right team and right technology.

Agile refers to a type of project management used often for software development. Tasks are divided into short phases of work and plans are frequently reassessed and adapted.

Here’s three ways an agile approach to Big Data Analytics can improve the success of an organisation.

 

#1 – DECISIONS & DELIVERY IN NEAR-REAL TIME

Data science allows us to make sense of the information we collect, and identify the valuable insights hidden in terabytes of structured and unstructured data. That being said, Big Data projects can be uncertain in nature if the right delivery methods are not used. This is where agile comes in.

“The principles and practices that are collected under the Agile umbrella all focus on validating assumptions as early as possible in the delivery lifecycle, significantly reducing the risk exposure as the project continues. By delivering the work in small increments, even with production-ready software, those assumptions are all validated early on. All code, design, architecture and requirements are validated every time a new increment is delivered. Even the plan is validated as teams get real and accurate data around the progress of the project.” – Gino Marck: Head of Agile Competency Center, EPAM Canada.

 

#2 – TEAM EFFICIENCY & COMMUNICATION

For a team to truly embrace agile, an interactive, adaptable and feedback-driven culture must be fostered in the organisation. The ability of a team to communicate progress and change direction when needed is crucial to the success of any Big Data project.

“For example, Ruben Perez, who runs a digital project management team at Scholastic Corporation, has his managers hold a daily scrum. When work is moving fast, you have to ensure that everyone is moving in the same direction, he says. “The scrum manager holds a 15-minute check-in every day to ensure that the tasks that have been slotted for a particular sprint are on track and that nothing is blocking forward progress. Anything that is standing in the way is assigned to someone to resolve—separately.” – The Economist.

 

#3 – IMPLEMENTING THE RIGHT TECHNOLOGY

“Shorter product cycles, compressed delivery times and pressures from a global economy require employees to thrive on change and be empowered to make decisions in near–real time. To power this sort of agility, companies must have the right technology—tools that allow for instant communication, collaboration and centralised platforms. And they’ve also got to establish and nurture an adaptive culture. Changing directions in a large organisation with long-established processes isn’t easy.” – The Economist.

Once the right culture is set in place, working with the right tools is what makes agile possible. An organisation must select the technology that will best cater to the transformation they’re after. Luckily, there’s no shortage of options. We’ve rounded up a few that you may find useful.

 

#1 – JIRA

With key features like issue tracking, bug tracking, kanban boards, workflows and the ability to customise the dashboard to meet the needs of your business, this software is the among the most popular project management tools available.

 

#2 – PLANBOX

Built as a four-level platform supporting Scrum Methodology, Planbox allows members across the business to collaborate, plan, and deliver projects, as well as enabling agile software development. Its features include release management, iterations, stories, backlog, prioritisation, scrum roles, sprints, estimated hours and story points.

 

#3 – ASANA

Asana is the ultimate progress tracker that helps you visualise your team’s work and follow up on individual tasks on a kanban board, calendar or list. It’s a flexible tool that adapts easily to an organisation’s scrum practices. With work efforts and communication in one place, team members can ensure that they have full clarity on sprint plans, milestones, launch dates and backlog.

 

For more resources, please see:

Powering The Agile Workplace

Big Data Analytics – What It Is And Why It Matters

How To Choose The Right Technology For Agile Transformation

 

Agile project management tools:

Asana

Planbox

Jira – Atlassian

 

To discuss this and other topics, please contact the team at Contexti – +61 2 8294 2161
| connect@contexti.com

Deep Learning Technologies Enabling Innovation

“Deep Learning has had a huge impact on computer science, making it possible to explore new frontiers of research and to develop amazingly useful products that millions of people use every day.” – Rajat Monga, Engineering Director at TensorFlow & Jeff Dean, Senior Fellow at Google.

With innovation driving business success, the demand for community-based, open-source software that incorporates AI & deep learning is taking over start-ups and enterprises alike. We’ve rounded up a few successful deep learning technologies that are making a big impact.

 

#1 – TensorFlow

TensorFlow is an open source software library that uses data flow graphs for numerical computation. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays communicated between them. With extensive built-in support for deep learning, TensorFlow can compute any algorithm that can be expressed in a computational flow graph.

“TensorFlow was built from the ground up to be fast, portable, and ready for production service. You can move your idea seamlessly from training on your desktop GPU to running on your mobile phone. And you can get started quickly with powerful machine learning tech by using our state-of-the-art example model architectures.” – Google Research Blog.

 

#2 – IBM PowerAI

Offering a collection of open-source frameworks for deep learning in one installable package, IBM Power AI claims to simplify  the installation and system optimisation required to bring up a deep learning infrastructure.

“PowerAI makes deep learning, machine learning, and AI more accessible and more performant. By combining this software platform for deep learning with IBM® Power Systems™, enterprises can rapidly deploy a fully optimised and supported platform for machine learning with blazing performance. The PowerAI platform includes the most popular machine learning frameworks and their dependencies, and it is built for easy and rapid deployment. PowerAI requires installation on IBM Power Systems S822LC for HPC server infrastructure.” – IBM

 

#3 – Intel Nervana

Nervana Systems, acquired by Intel last year, is now known as Intel Nervana and referred to as ‘the next big shift inside corporate data centers.’

“Nervana has built an extensive machine learning system, which runs the gamut from an open-sourced software platform all the way down to an upcoming customised computer chip. The platform is used for everything from analysing seismic data to find promising places to drill for oil to looking at plant genomes in search of new hybrids.” – Aaron Pressman: Senior Writer at Fortune.

This state-of-the-art deep learning system is made up of curated, enterprise-grade collections of the world’s most advanced deep learning models and is updated on a regular basis.

“The Intel® Nervana™ Deep Learning Studio, a suite of tools with an easy-to-use interface, dramatically simplifies the deep learning process and accelerates time-to-solution. After you import your data, you can extend one of our state-of-the-art models or build your own. Then, you can kick off training with single click and track progress on the dashboard. All the capabilities of the platform are also accessible via a powerful command line interface.” – Intel Nervana.

 

#4 – NVIDIA Deep Learning SDK

‘The NVIDIA Deep Learning SDK provides high-performance tools and libraries to power innovative GPU-accelerated machine learning applications in the cloud, data centers, workstations, and embedded platforms.’ – NVIDIA.

Offering a comprehensive development environment for building new GPU-accelerated deep learning algorithms, and the inclusion of libraries for deep learning primitives, inference, video analytics, linear algebra, sparse matrices, and multi-GPU communications, your business could dramatically increase the performance of existing applications.

“With the updated Deep Learning SDK optimised for Volta, developers have access to the libraries and tools that ensure seamless development and deployment of deep neural networks on all NVIDIA platforms, from the cloud or data center to the desktop to embedded edge devices. Deep learning frameworks using the latest updates deliver up to 2.5x faster training of CNNs, 3x faster training of RNNs and 3.5x faster inference on Volta GPUs compared to Pascal GPUs.” – NVIDIA.

 

 

For more resources, please see below:

IBM Power AI

Intel Nervana Platform

Why Deep Learning Is Suddenly Changing Your Life

Nividia Accelerated Computing – Deep Learning Software

Why Intel Bought Artificial Intelligence Startup Nervana Systems

TensorFlow – Google’s Latest Machine Learning System, Open Sourced For Everyone

Intel Is Paying More Than $400 Million To Buy Deep-Learning Startup Nervana Systems

PowerAI: The World’s Fastest Deep Learning Solution Among Leading Enterprise Servers

Data’s Growing Potential To Transform Business

“Big Data does not only refer to online activity but also to behaviour offline, including use of credit cards or even smartphones, which send GPS locations and records behaviour. The existence of large volumes of data that can be used for different applications provides those willing to data mine and analyse with several opportunities.” – Daniel Abela: Owner & Managing Director at Redorange.

In the past few years, Big Data analytics has become a game-changer for many businesses worldwide, with profitable outcomes achieved in successful startups like Treasure Data and MapD, and large enterprises like Amazon and Apple. With new and innovative technologies continuing to launch at a rapid pace, the potential for growth won’t be slowing down anytime soon.

“The integrated use of analytics, Big Data, the cloud, the Internet of Things (“IoT”), mobile, and application development—is driving change at unprecedented rates. Our digital economy is subject to Moore’s law and digital transformation has become the new normal.” – Forbes.

Here’s some examples of how you can use data analytics to grow your business.

 

#1 – Business Intelligence For Better Decision-Making

“No matter what BI application is used, the reality is that organisations are continuously searching for ways to get more value out of their data. BI provides one of the best ways to transform data sources into interactive information that can lead to better decision making and planning.” – Lyndsay Wise: Solution Director at Information Builders.

The aim of business intelligence is to generate value, insight and support better decision-making. With a myriad of BI tools in the market delivering real-time insights on user-friendly dashboards, businesses have more power than ever when it comes to leveraging information to their advantage. We’ve rounded up a few successful ones to help you decide which tool is right for your business.

 

Qlik Sense

With the ability to easily combine your data sources and get detailed reports in an instant, Qlik has been deemed as an effective and user-friendly analytics tool by its users.

“With the Associative engine at its core, Qlik Sense lets you discover insights that query-based BI tools simply miss. Freely search and explore across all your data, instantly pivoting your analysis when new ideas surface. You’re not restricted to linear exploration within partial views of data. And you get total flexibility with a cloud-ready data analytics platform that supports the full spectrum of BI use cases – ideal for any analyst, team or global enterprise.” – Qlik.

 

Sisense

“Designed to be used by people who need to consume and analyse large amounts of data but have little or no prior experience in data crunching.” – Forbes.

An industry leader in business intelligence tools, this agile tool lets you analyse and visualise both big and disparate datasets and adapts to the needs of your business.

“Our Single-Stack™ architecture takes you from data integration to visualisation with a single BI software solution, eliminating the need to use additional tools.” – Sisense.

 

Microsoft Power BI

“It is the exact visually-appealing, dynamic, and user-friendly tool every developing company needs, and has thus brought a number of critical benefits.” – financesonline.com.

Power BI is a set of business analytics tools designed to analyse data, share insights, provide a 360-degree view of important metrics available on all devices, receive real-time updates and provide hundreds of connections to popular business apps.

“Power BI can unify all of your organisation’s data, whether in the cloud or on-premises. Using the Power BI gateways, you can connect SQL Server databases, Analysis Services models, and many other data sources to your same dashboards in Power BI. If you already have reporting portals or applications, embed Power BI reports and dashboards for a unified experience.” – Microsoft Power BI.

 

#2 – Digitisation Of Business Processes For Operational Efficiency & Customer Retention

“Spoiled by user experiences on Google and Amazon, people are increasingly demanding enhanced digital access to their records, as well as instantaneous access to the services they’re buying. This increases the pressure on traditional companies and leaves them vulnerable to disruption.” – Sharon Fisher: Content Strategist at The Economist Group.

Digitisation of people and processes is the future of business. The end-to-end customer experience design of your business can make or break your competitive edge. As demands and expectations grow, automation and optimisation become key to customer retention and organisational productivity.

“Intuitive interfaces, around-the-clock availability, real-time fulfillment, personalised treatment, global consistency, and zero errors—this is the world to which customers have become increasingly accustomed. It’s more than a superior user experience, however; when companies get it right, they can also offer more competitive prices because of lower costs, better operational controls, and less risk.” – McKinsey & Company.

Using Big Data analytics to implement automated operational strategies into your business model can be both a cost and time effective strategy, as well as an enabler for revenue growth.

“Automation gives fast growing companies the tools to keep up, but the how-to-get-there can seem like a daunting task. Any successful owner, founder, or CEO knows you have to plan for growth. That plan should include finding the right technology that can scale with your business — and automation must be integral to that plan.” – Salesforce.

 

 

#3 – Innovation & Growth Using Big Data Analytics Powered By Cloud Computing

“Whether making the decision to move to the cloud is instigated by economics or the ever-increasing speed of business, organisations need to get data-driven faster, and turning to the Cloud sooner rather than later may just be the answer.” – Dataversity.

Companies who maximise their use of analytics have a faster rate of growth and are in a stronger position to innovate than those who don’t. Using the cloud as a platform for speed, scale, customer engagement and innovation has increased the performance of the companies below.

 

Atlassian – “Aussie startups are thriving thanks to cloud technology services. Atlassian, a company that sells $100m worth of software to 130 different countries per year is an Australian startup success story. Atlassian has grown from a tech startup making clever use of cloud technologies, to an internationally renowned, billion-dollar company.” – Amazon Web Services.

Founded in 2002, Atlassian is a software company with various collaboration tools used by enterprises and startups worldwide.

“Atlassian uses AWS to scale its issue-tracking software applications faster than before, provide improved services to tens of thousands of global customers, and enhance its disaster recovery and availability. The Australia-based organisation provides software that helps developers, project managers, and content managers collaborate better. Atlassian uses Amazon EFS to support customers deploying JIRA Data Center on AWS, and also runs an internal issue-tracking application platform on AWS.” – Amazon Web Services.

 

Pearson – Founded in 1998, Pearson is a global online education provider that offers learning resources to a wide range of people, from preK-12 education and higher education to industry professionals.

“Pearson is using the cloud to transform the way it delivers education worldwide. The cloud is enabling Pearson to establish a more flexible global hybrid infrastructure with common systems and processes, which frees up resources to invest in new, more web-oriented educational products that deliver measurable outcomes for learners. This is part of an enterprise-wide business transformation that will help accelerate the company’s shift towards fast-growing markets — like South Africa and China — and educational products that are increasingly digital in nature.” – Forbes.

 

Judo Capital – “Working with cloud based services and capabilities, provided by Itoc, has enabled us to remain focused on our true mission, while achieving our vision of an IT-less future.” – Graham Dickens: Chief Technology Officer at Judo Capital.

Judo Capital, built by a small group of highly experienced bankers, is a specialist financier designed to address the financial needs of Australian SMEs. Using Itoc, a provider of a range of cloud and DevOps services, they have been able to leverage growth through better decision-making.

“Designed and built from the ground up in just 6 months, the Judo team and their technology partners have created a new breed of platform, a true ecosystem in the cloud that supports real time effective distribution of information, transparent communication and decision making. The result of which empowers Judo bankers and brokers to deliver an unrivalled service and provide customers with the opportunity to gain insight and transparency into the renowned ‘dark art’ that is today’s customer experience of SME lending.” – Richard Steven: CEO of Itoc.

 

 

For more resources, please see below:

Big Data, Huge Opportunities

Big Data & Advanced Analytics

How To Digitise Your Business In Simple Steps

Accelerating The Digitisation Of Business Processes

Why Automation Is Essential To Your Business Growth

Four Ways To Innovate Using Big Data And Analytics

Time To Digitise Business Processes, McKinsey Says

Business Transformation: How Big Data Analytics Helps

8 Ways You Can Grow Your Business Using Data Science

Four Reasons Why Big Data Analytics In The Cloud Makes Sense Now

Business Intelligence, Data Transformation And Better Decision Making

Using Rapid Process Digitisation To Transform The Customer Experience

The Importance Of Big Data and Analytics In The Era Of Digital Transformation

How Digital Disrupts Operations, Business Processes And Customer Experience

Seven Business Process Automation Benefits That Make Your Company More Money

 

Business Intelligence Tools

Sisense

Qlik Sense

Microsoft Power BI

15 Business Intelligence Tools For Small And Big Businesses

 

Businesses Leveraging Cloud Computing

Itoc

Pearson

Atlassian

Judo Capital

Amazon Web Services

Case Study: Unleashing The Potential Of Australian Businesses

The Advantages Of Cloud Computing For Startups

Three Companies That Transformed Their Businesses Using Cloud Computing

Cloudera Acquires Fast Forward Labs To Enhance Machine Learning & AI Research

Given the speed of innovation in the digital realm, it’s exciting to see our partner Cloudera continue to stay ahead of the game with their recent acquisition of Fast Forward Labs (now known as Cloudera Fast Forward Labs), a top-tier applied research and advisory services company.

Cloudera Fast Forward Labs, will concentrate on practical research into new approaches to data science and applying research to business problems that are broadly applicable to a variety of industries and applications.

For the full story, check out Cloudera’s Recent Business & Financial Highlights.

For more resources, please see below:

Data Empowering Artificial Intelligence & Machine Learning

How Big Data Is Changing The Customer Experience & Improving SEO

Cyber Security Strengthened By Big Data Analytics & Machine Learning