Preparing Your Business For Digital Transformation With Data Science & Cloud Computing

“Modern enterprise technologies generate vast amounts of data, which can be challenging and time-consuming to analyse. By building data science models that are accessible, meaningful, and actionable, however, you can spot new opportunities quickly and speed up decision-making.” – The Infor Blog.

When it comes to speed of execution and reliability of insights, data science is a key component for success. Analysing data patterns allow businesses to build models that create forecasts of what can happen in different scenarios, create solutions and generate actionable insights.

 

THE KEY DRIVERS OF DIGITAL TRANSFORMATION

“Digital transformation can be defined as the acceleration of business activities, processes, competencies and models to fully leverage the changes and opportunities of digital technologies and their impact in a strategic and prioritised way.” – Mark Edmead: IT Transformation Consultant & Trainer at MTE Advisors.

Organisations are faced with the constant challenge of adapting to a changing business landscape in order to remain competitive. This includes keeping up with demand, changes in customer behavior and adopting new and innovative technologies into the business model. The key drivers behind digital transformation include profitability, scalability, and added value propositions to product and service offerings.

“Enterprises should be able to deliver custom applications at the speed of ideas. That’s the way to stay ahead in competition in today’s world. Lowering operational costs and enhancing customer experience is the core of digital transformation.” – Forbes.

When it comes to implementing digital transformation effectively, it’s not just about technology, it’s about building the right team. Organisational culture, the right mindset, good communication skills, and a clear understanding of the digitisation strategy are key players in the speed and effectiveness of digital transformation. Employees that are empowered by IT leaders and have received the right training feel more encouraged and enabled to embrace technology and data-driven decision making.

This is why it’s important to address any skill gaps before digital transformation takes place, and to also have a criteria of skill sets required for new employees, based on the goals your organisation is trying to achieve.

“The people you need to hire are the flexible, innovative and entrepreneurial ones. They’re not afraid to fail. They can pick up new techniques very quickly. They’re curious.” – Talent Sonar.

 

DATA SCIENCE IN THE CLOUD

“Data science is enabling the next generation of enterprise software, resulting in solutions that tell users what is going to happen and what they should do about it today.” – Ben Rossi: Contributor at Information Age.

Exploding data volumes are increasing the complexity of analysis, and with most data scientists running tools like AWS Machine Learning, Azure, Python and R in the cloud, it’s safe to say that data science and cloud computing go hand-in-hand.

Many organisations are investing a lot of time and resources on Big Data and making sure it stays in the cloud, in order to experience benefits like flexibility, ability to collaborate, reduced IT costs, and easy access to data.

“Businesses need to be continuously embracing new online marketing channels, bringing new digitally-evolved products to market, refreshing the value propositions of their offerings, and utilising cloud technologies to enable scaling and globalisation at pace.” – Conservit.

 

DATA STORAGE & ACCESSIBILITY

“Processing data and shifting it to Cloud organisations avails two benefits, including tackling large sets of data for decision making and reducing the overall cost of infrastructure.” – Edureka!

Data storage is a challenge for many businesses, but Cloud computing has made storing and analysing data much easier by simplifying IT management, data maintenance and infrastructure updates.

“Value of data is dependent on frequency and speed of access needed to deliver business requirements. Digital enterprises operate with radically different datanomics than conventional physical businesses. Here, digital information is the business.Yes, that means that there is exponentially more data to store and manage. But it also means a fundamental difference in how that data needs to be stored and managed.” – Ash Ashutosh: Contributor at InfoWorld,

Cloud computing, built around a series of hardware and software that can be accessed remotely through any web browser, can greatly assist businesses looking to improve their service offerings through accessible, machine readable data.

“Cloud computing offers your business many benefits. It allows you to set up what is essentially a virtual office to give you the flexibility of connecting to your business anywhere, any time. With the growing number of web-enabled devices used in today’s business environment (e.g. smartphones, tablets), access to your data is even easier.” – Business Queensland.

 

 

For more resources, please see below:

Benefits Of Cloud Computing

Why Your Business Needs Digital Transformation

5 Effective Steps To Hire For Digital Transformation

Why Digital Transformation Is Not Just About Technology

The Importance Of Data Science With Cloud Computing

Running Scalable Data Science on Cloud With R & Python

How Digital Transformation Disrupted The Storage Industry

How To Digitally Transform Your Business With Data Science

Digital Transformation: Why It’s Important To Your Organisation

Digital Transformation and Innovation In Today’s Business World

How Data Science Is The Driving Force Behind Successful Digital Transformation

Blockchain Technology Securing The Internet Of Things

“If we are most likely to understand the Internet of Things (IoT) by describing how it relates to objects we use every day, such as a toaster or bicycles, we miss the big picture: a futuristic global network of connected devices, transforming industrial and business processes in a way that we cannot yet comprehend.” – Rhian Lewis: Co-Founder of Count My Crypto.

This revolutionary concept of IoT is already well under way, and the multitude of smart devices connected to it could transform businesses, homes and cities. But without the right security strategy, the more devices we connect, the more problems we encounter.

 

SECURITY

“The intersection between IoT and Blockchain is a fascinating area. Gartner has predicted there will be 20.4 bln connected devices by 2020 with smaller, more efficient sensors and microprocessors offering the potential for use cases of which we can barely dream today. Decentralised architectures mitigate against single points of failure while providing standard protocols for devices to discover each other and communicate.” – The Cointelegraph.

With security concerns on the rise, blockchain technology is not only a safety measure, it’s a cost-saving and error-reducing opportunity.

“Blockchain’s potential to transform the way we think about IoT security is actually a side effect of an even greater opportunity: to rethink problems with online identity that have been festering for decades.” – The Wall Street Journal.

Blockchain, as a way to structure data, is allowing entities to share a digital ledger across a network of computers without the need for a central authority. No single party has the ability to tamper with records. Encryption enables the entities to share a common infrastructure for database retention. The blockchain database is not stored in one location, meaning that records are truly public and can be verified easily. With no centralised version of this information, a hacker can’t corrupt it.

“Although IoT devices are miracles of engineering, they are still underpowered compared to the hardware powering successful blockchains.” – Forbes.

 

IMPLEMENTING BLOCKCHAIN TECHNOLOGY INTO YOUR BUSINESS

“The distributed ledger technology that started with bitcoin is rapidly becoming a crowdsourced system for all types of verification. Could it replace notary publics, manual vote recounts, and the way banks manage transactions?” – strategy-business.com.

Blockchain is being used by businesses for a myriad of things like accepting payments, hiring and even paying wages with Bitwage.

“The clearest and easiest way to start using blockchain tech is to start accepting Bitcoin – or another cryptocurrency – for payments. These payments are fine for peer-to-peer transactions, but they work even better for small businesses.” – Capterra.

Bitcoin is a worldwide cryptocurrency and digital payment system. Units of currency are regulated using encryption techniques to verify the transfer of funds, operating independently of a central bank. Bitcoin is received, stored, and sent using software known as a Bitcoin Wallet. Getting started with bitcoin is relatively easy. By simply downloading the Bitcoin Wallet of your choice, you can send and receive bitcoin.

“This distributed ledger — the first blockchain ledger ever created was for bitcoin, and it set the pattern for others — represents the most innovative and potentially influential aspect of the technology. Participants interact with one another using pseudonyms, and their real identities are encrypted. The ledger uses public-key encryption, which is virtually impossible to break, because a message can be unlocked only when a public and a private element (the latter held only by the recipient) are linked.” – strategy-business.com.

Although controversial, businesses around the world are seeing the potential that this technology has to not only how we handle payments, but transform how we do business in every way, from how stock exchanges operate, to re-shaping capital markets, to smart contracts. But the global blockchain revolution won’t happen overnight.

“Today, you have to assemble a lot of pieces by hand if you want to develop a blockchain platform, just like how, in 1995 or 1996, if you wanted to publish a website, you had to work with html. You had a page editor where you would hand write the html page almost line by line. No one does that anymore. Now you can create a web page without touching a line of code with Squarespace, WordPress, Tumblr, etc. That’s where we need to go.” – Laura Shin: Senior Editor at Forbes.

 

 

For more resources, please see below:

 

The Business Blockchain

Bitcoin – The Internet Of Money

A Strategist’s Guide To Blockchain

4 Critical Security Challenges Facing IoT

What Blockchain Is And What It Can Do

3 Ways To Use Blockchain In Your Business This Year

How Blockchain Could Revolutionise The Internet Of Think

Could Blockchain Technology Help You Find Better Employees?

Looking To Integrate Blockchain Into Your Business? Here’s How

What Is Blockchain Technology? A Step-By-Step Guide For Beginners

Are We Creating Insecure Internet Of Things (IoT)? Security Challenges & Concerns

Blockchain: Wall Street’s Most Game-Changing Technology Advance Since The Internet

Insights On Big Data For Marketing, Sales & E-Commerce

#1 – TARGETING THE OMNI-CHANNEL CUSTOMER

“The use of Big Data has become a critical force in growing revenues. Big Data Analytics is helping retailers stay in front of a new breed of consumer, the omni-channel shopper.” – Durjoy Patranabish: Former Senior Vice President of Analytics at Blueocean Market Intelligence.

Over the last decade, the field of marketing has undergone rapid changes, moving from mass-marketing to a more personalised, individual communication approach. Analytics tools allow us to segment customers based on preferences, and track the progress of our marketing campaigns.

“Consumers can now engage with a company in a physical store, on an online website or mobile app, through a catalog, or through social media. They can access products and services by calling a company on the phone, by using an app on their mobile smartphone, or with a tablet, a laptop, or a desktop computer.” – Mike Stocker: Vice President of Business Development at Vidyard.

With multiple channels available to purchase from, marketers are faced with the challenge of providing consistency in the customer experience at every potential touchpoint of their purchasing journey. From monitoring web traffic on Google Analytics to launch promotions at optimal times, to investing in SEO services to boost keyword rankings, to building customer journey maps, marketers need to be in the know-how about what motivates their customers in order to deliver what they’re looking for.

 

#2 – WHAT GETS MEASURED, GETS MANAGED

“The most successful companies are digging deep into the data driven research available to them, giving them a leg up on customer retention and bolstering the bottom line.” – Jennifer Havice: Website Copywriter & Online Marketing Strategist at Make Mention Media & Communications.

Big or small, every business can reap the benefits of data analytics tools that give you the insights you need to increase your marketing ROI. We’ve rounded up some of the most popular tools in the industry.

 

Mixpanel

A platform for following the digital footprint of each of your users across both mobile and web devices. This tool allows for for flexibility and customisation, no matter what your role within the business, so you can get the precise knowledge you’re after about your product or service.

 

Kissmetrics

A popular customer intelligence web analytics platform to help track the customer journey, aimed at businesses looking to optimise their digital marketing and boost conversion rates.

 

Google Analytics

A seamless, all-inclusive picture of your business performance. Google Analytics shows you how your campaigns are doing, which customer channels have the highest conversion rate, and allows to set goals and targets, so you you can track your progress over time.

 

Kapost

Helping businesses “turn content into customers,” this platform is used to drive content operation and realise your b2b marketing strategy. It can be integrated with tools like WordPress, Hootsuite and Marketo.

 

#3 – IDENTIFYING OPPORTUNITIES

“The biggest challenge for most eCommerce businesses is to collect, store and organise data from multiple data sources. There’s certainly a lot of data waiting to be analysed and it is a daunting task for some E-commerce businesses to make sense of it all.” – Jerry Jao: CEO & Founder of Retention Science.

Not only does data analytics increase revenue potential with your current customers, it can also be used to identify and attract new markets to tap into.

“Large online vendors can scale their offerings with Big Data and meet specific customer needs. But Big Data also allows to predict customer needs and enable a future optimisation of the product portfolio. So with Big Data, it is possible to optimise the stock costs.” – Big Data Made Simple.

Online retailers can now make better informed decisions while also forecasting for the future. Wouldn’t you love to know what you’re customers would like to buy in advance, and how much they’d be willing to spend? with predictive analytics, you can.

Predictive analytics involves extracting information from your existing data to determine patterns and predict future outcomes and trends. Platforms like RapidMiner and Lattice help identify potential anomalies, service opportunities, reduce the uncertainty of outcomes and score better sales leads.

 

 

 

For more resources, please see below:

 

The Omni-Channel Customer

What Is Omnichannel?

Targeting Omni-Channel Shoppers

The Definition of Omni-Channel Marketing – Plus 7 Tips

Ten Ways Big Data Is Revolutionising Marketing & Sales

 

Marketing Tools

Kapost

Mixpanel

Kissmetrics

8 Big Data Solutions For Small Businesses

Big Data Trends: Top Eight Analytics Lessons For Business

4 Marketing Analytics Tools That Are Shaping The Industry

 

Identifying Opportunities

Lattice Engines

RapidMiner: Data Science Platform

Why Big Data Is A Must In E-Commerce

How Predictive Analytics Is Transforming eCommerce & Conversion Rate Optimisation

 

 

 

Career Opportunity For Linux Administrators At Contexti | Big Data Analytics

Location: Sydney, Australia

 

ABOUT US

Contexti is a specialist Big Data Analytics Solutions company serving the Australian market. With strong partnerships with AWS, Cloudera, Talend and Mesosphere, we provide training, consulting and managed services for some Australia’s leading enterprises where data is at the heart of their business transformation.

We are a small but growing Sydney based team; most work is performed from our CBD office location, but occasionally we will work from customer sites. We prioritise cultivation of positive relationships with customers and seek to provide a good team atmosphere with a healthy work-life balance. While not for everyone, a significant portion of us are also on a quest to identify and consume the best Ramen and Laksa Sydney has to offer.

 

THE OPPORTUNITY

We’re looking for an experienced Linux Administrator who will be responsible for maintaining, designing, implementing, and monitoring predominantly cloud based systems. Collaboration with other team members is essential as we continue to develop automation strategies and deployment processes. You will become an integral part of the team, taking ownership of implementation work as well as working ad hoc problems through to resolution.

Your responsibilities:

  • Implement, maintain and support solutions that enable positive outcomes for our customers.
  • Take on complex integration problems making diverse application components work together.
  • Help tune performance and ensure high availability of infrastructure.
  • Design and develop infrastructure monitoring and reporting tools.
  • Develop and maintain configuration management solutions.
  • Develop test automation frameworks in collaboration with rest of the team.
  • Create tools to help teams make the most out of the available infrastructure.

 

ABOUT YOU

The person:

  • Looking for purpose in your work and the company you work for
  • You’re ready to learn, grow and contribute
  • You love to help customers and team members

 

You have the following skills:

  • Experience with Linux servers in virtualized environments.
  • Familiarity with the fundamentals of Linux scripting languages including Bash and Python.
  • Experience installing, configuring, and maintaining services such as Apache Httpd, MySQL, nginx, etc.
  • Exposure to Kerberos, and better still experience integrating Linux with Active Directory, e.g. SSSD, Centrify, etc.
  • Basic knowledge of configuration management tools (e.g as Ansible, Puppet and Chef).
  • Exposure to infrastructure versioning, provisioning and continuous integration tools (e.g Jenkins, HashiCorp TerraForm/Vagrant/Packer).
  • Familiarity with load balancing (e.g. HAProxy), firewalls, etc.
  • Experience with containerisation technologies, such as Docker, Apache Mesos, DC/OS, etc.
  • Experience with prominent core AWS services (VPN, VPC, EC2, EBS, S3, IAM, CloudWatch etc).
  • Hadoop experience would be an added bonus, but is not a requirement – you can learn this from us.
  • Most likely you will have a Computer Science Degree, you will certainly have relevant industry experience.

 

HOW TO APPLY

  • You must hold the right to work in Australia to be considered for this role.
  • Please send your resume and short cover note to jobs@contexti.com

Note to Recruiters – We will be filling these roles directly.

For more resources, please see below:

How To Succeed On Your Big Data Journey
5 Tips On How To Land A Big Data Job In Australia
Data & Analytics Australian Recruitment Market Insights By FutureYou

 

3 Strategies For Getting The Most Value From Your Data Lake

“Big Data’ and ‘data lake’ only have meaning to an organisation’s vision when they solve business problems by enabling data democratisation, re-use, exploration, and analytics.” – Carlos Maroto: Technical Manager at Search Technologies.

A data lake is a storage repository that acts as the central source of all your organisation’s current and historical data, both structured and unstructured. This data is transformed as it moves through the pipeline for things such as analysis, creating quarterly and annual reports, machine learning and data visualisation. The information contained in a data lake can be highly valuable asset, however, without the right structure, your data lake could turn into a data swamp.

Here’s three strategies for getting the most value from your data lake.

 

#1 – BUSINESS STRATEGY & TECHNOLOGY ALIGNMENT

“It’s important to align goals for your data lake with the business strategy of the organisation you’re working to support.” – Bizcubed.

What are the business goals you’re trying to achieve with your data lake? Operational efficiency? Better understanding of your customers? Will your current infrastructure help you achieve this while also maximising your profits? Aligning your goals with the technology you’re planning to implement will not only help you articulate what problem you’re trying to solve, but also improve your chances of gaining executive buy-in and winning the support of your team. The better the plan, the easier it is to identify possible roadblocks and the higher the chance of success.

“As technology teams continue to be influenced by the hype and disruption of Big Data, most fail to step back and understand where and how it can be of maximum business value. Such radically disruptive new business processes can’t be implemented without knowledge gathering and understanding how Big Data technology can become a catalyst for organisation and cultural change.” – Thierry Roullier: Director of Product Management at Infogix, Inc.

 

#2 – INTEGRATION & ARCHITECTURE

“You need to be able to integrate your data lake with external tools that are part of your enterprise-wide data view. Only then will you be able to build a data lake that is open, extensible, and easy to integrate into your other business-critical platforms.” – O’Reilly.

Technology is moving at a rapid place.The tools you use in your business may not cooperate well with your data lake, and may not support the data architectures of tomorrow. During the implementation process, one of the first things to look at is how adaptable your long-term technology investments are.

Big Data architectures are constantly evolving, and it’s important to select flexible data processing engines and tools that can handle changes to security, governance and structure without being too costly to the organisation. Before implementing anything, you need to have a clear vision of what you want the end technical platform to look like, and what components you will need to make that happen.

“Modern data onboarding is more than connecting and loading. The key is to enable and establish repeatable processes that simplify the process of getting data into the data lake, regardless of data type, data source or complexity – while maintaining an appropriate level of governance.” – Bizcubed.

 

#3 – DATA VIRTUALISATION & DEMOCRATISATION

“ Data virtualisation involves abstracting, transforming, federating and delivering data from disparate sources. The main goal of data virtualisation technology is to provide a single point of access to the data by aggregating it from a wide range of data sources.” – TechTarget.

Data lakes and data virtualisation tools work well together to solve different problems and provide a layer of intelligence that results in more agility and adaptability to change.

“ As an example, a virtual layer can be used to combine data from the data lake (where heavy processing of large datasets is pushed down) with golden records from the MDM that are more sensitive to stale copies. The advance optimisers of modern data virtualisation tools like Denodo make sure that processing is done where it is more convenient, leveraging existing hardware and processing power in a transparent way for the end user. Security and governance in the virtual layer also add significant value to the combined solution.” – datavirtualizationblog.com.

Data democratisation is the ability for information in a digital format to be accessible to the average end user. The goal of data democratisation is to allow non-specialists to be able to gather and analyse data without requiring outside help.

“Data must be freed from its silos. Today, it resides in a variety of independent business functions, such as HR, manufacturing, supply chain logistics, sales order management and marketing. To get a unified view of this data, businesses are engaging in a variety of ad-hoc, highly labor-intensive processes.” – Computer Weekly.

 

For more resources, please see below:

Best Practices For Data Lakes

How To Build A Successful Data Lake

Five Keys To Creating A Killer Data Lake

Avoiding The Swamp: Data Virtualisation & Data Lakes

Democratising Enterprise Data Access: A Data Lake Pattern

How To Successfully Implement A Big Data/ Data Lake Project

Top Five Differences Between Data Lakes & Data Warehouses

 

2018 Big Data Predictions

“There are only two certainties in Big Data today: It won’t look like yesterday’s data infrastructure, and it’ll be very, very fast.” – Matt Asay: Head of Developer Ecosystem at Adobe.

Technology and the power of data science have created huge leaps of growth for businesses who utilise it, and it’s no surprise that the mass increase of worldwide data will mean that Big Data will encounter some big changes in the year ahead.

 

#1 – COGNITIVE TECHNOLOGIES

Cognitive technologies are constantly evolving, and becoming more and more capable of performing tasks that require human intelligence.

“It is now possible to automate tasks that require human perceptual skills, such as recognising handwriting or identifying faces, and those that require cognitive skills, such as planning, reasoning from partial or uncertain information, and learning.” – Deloitte University Press.

Cognitive systems like IBM Watson are improving business products, processes and insights by allowing systems to interact with humans more naturally, and understand complex questions posed in natural language.

“Computing systems of the past can capture, move and store unstructured data, but they cannot understand it. Cognitive systems can. The application of this breakthrough is ideally suited to address business challenges like scaling human expertise and augmenting human intelligence.” – IBM.

 

#2 – PRESCRIPTIVE ANALYTICS

“If analytics does not lead to more informed decisions and more effective actions, then why do it at all?” – Mike Gualtieri: Vice President & Principal Analyst at Forrester Research.

Informed decisions lead to better results. Prescriptive analytics incorporates both predictive and descriptive analytics, and is used to determine the best course of action to take in a given situation. It involves a combination of mathematics, analytics and experimentation that help businesses make
better decisions based on logic. When used correctly, it can help businesses optimise production and enhance the customer experience.

“Prescriptive analytics predicts not only what will happen, but also why it will happen providing recommendations regarding actions that will take advantage of the predictions.” – halobi.com

 

#3 – FAST DATA IS THE NEW BIG DATA

“The argument is that big isn’t necessarily better when it comes to data, and that businesses don’t use a fraction of the data they have access to. Instead, the idea suggests companies should focus on asking the right questions and making use of the data they have — big or otherwise.” – Forbes.

Fast data applies Big Data Analytics to smaller datasets in near-real or real time to mine both structured and unstructured data and quickly gain insight on what action to take. With streaming systems like Apache Storm and Apache Kafka, the value of fast data is being unlocked.

“As organisations have become more familiar with the capabilities of Big Data Analytics solutions, they have begun demanding faster and faster access to insights. For these enterprises, streaming analytics with the ability to analyze data as it is being created, is something of a holy grail.” – Dana Sandu: Marketing Evangelist at SQLstream.

 

#4 – MACHINE LEARNING & AUTOMATION

“It’s possible to quickly and automatically produce models that can analyse bigger, more complex data and deliver faster, more accurate results – even on a very large scale. The result? High-value predictions that can guide better decisions and smart actions in real time without human intervention.” – sas.

The learning capabilities of machines are growing at a large scale, and connecting people, processes and products in new and exciting ways.

“Your digital business needs to move towards automation now while ML technology is developing rapidly. Machine learning algorithms learn from huge amounts of structured and unstructured data, e.g. text, images, video, voice, body language, and facial expressions. By that it opens a new dimension for machines with limitless applications from healthcare systems to video games and self-driving cars.” – Ronald Van Loon: Director at Advertisement.

Today, machine learning is transforming online businesses and being used by organisations for a myriad of things like fraud detection, real-time ads, pattern recognition, speech analysis and spam-filtering. But in 2018, machine learning is said to become faster and smarter than ever before, while also making better predictions for the future.

“Now machine learning seems to offer a solution for demand forecasting. With the inherent capability to learn from current data, machine learning can help to overcome challenges facing businesses in their demand variations.” – Dataversity.

 

#5 – AI ENHANCING CYBER SECURITY

“Artificial Intelligence is looking quite interesting for 2018 and the near future with the attempts to apply reinforcement learning to problems, which enables machines to model human psychology in order to make better predictions; or contesting neural networks with generative adversarial networks algorithms which requires less human supervision and enables computers to learn from unlabeled data; making them more intelligent.” – Exastax.

With capabilities of problem-solving and modeling human psychology, enhancements in AI are also said to be a defence mechanism for safeguarding data in the near future.

“Ironically, our best hope to defend against AI-enabled hacking is by using AI. AI can be used to defend and to attack cyber infrastructure, as well as to increase the attack surface that hackers can target, that is, the number of ways for hackers to get into a system. Business leaders are advised to familiarise themselves with the cutting edge of AI safety and security research.” – Harvard Business Review.

 

For more resources, please see below:

 

2018 Big Data Predictions

Big Data Changes Coming In 2018

Why Big Data Is Important To Your Business

Five Key Predictions For Data & Analytics Through 2020

17 Predictions About The Future Of Big Data Everyone Should Read

 

Cognitive Technologies

How To Get Started With Cognitive Technology

Cognitive Technologies: The Real Opportunities For Business

KPMG Invests In Game-Changing Cognitive Technologies For Professional Services

 

Prescriptive Analytics

What Exactly The Heck Are Prescriptive Analytics?

Descriptive, Predictive And Prescriptive Analytics Explained

 

Fast Data

Fast Data: The Next Step After Big Data

The Future Of Fast And Big Data Technologies

 

AI & Cyber Security

Cyber Intelligence: What Exactly Is It?

Top 10 Security Predictions Through 2020

Five Trends In Cyber Security For 2017 And 2018

The Future Of Artificial Intelligence: Prediction For 2018

AI Is The Future Of Cyber Security For Better And For Worse

18 Artificial Intelligence Researchers Reveal The Profound Changes Coming To Our Lives

Cyber Threats Are Growing More Serious, And Artificial Intelligence Could Be The Key To Security

 

Machine Learning & Automation

Machine Learning & Automation – What It Is & Why It Matters

The Future Of Machine Learning: Trends, Observations & Forecasts

 

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

Data Empowering Artificial Intelligence & Machine Learning

#1 – FASTER & SMARTER DECISIONS

Digital transformation through Artificial Intelligence has led to more agile, productive and smarter businesses. Automation and machine learning are helping companies save time and money, personalise customer service and detect fraud while also improving work processes and expanding top-line growth.

“Artificial Intelligence or AI, has become pervasive in business in every industry where decision making is being fundamentally transformed by Thinking Machines. The need for faster and smarter decisions and the management of Big Data that can make the difference is what is driving this trend.” – James Canton: CEO & Chairman of The Institute of Global Futures.

 

#2 – DATA-DRIVEN AI & MACHINE LEARNING

“Machine Learning is a current application of AI based around the idea that we should really just be able to give machines access to data and let them learn for themselves.” – Bernard Marr: Founder & CEO of Bernard Marr & Co.

With data science reaching new capabilities for industry disruption, the correlation of data and Artificial Intelligence has powerful potential; and with advancements in machine learning becoming more accessible, it can now be applied to resolve actual business problems.

“The ability to access large volumes of data with agility and ready access is leading to a rapid evolution in the application of AI and machine-learning applications.” – Randy Bean: CEO of NewVantage Partners.

 

#3- ARTIFICIAL INTELLIGENCE VS. HUMAN INTELLIGENCE

“There have been multiple reports recently which claim that a major part of the human workforce will be replaced by automatons and machines in the years to come. With excessive research and development being conducted in the field of artificial intelligence, many fear that a major job crisis will unfold since multiple jobs are more accurately and efficiently performed with the utilisation of machines.” – Brent Morgan: Founder of Transcendent Designs LLC.

With all the benefits of Artificial Intelligence comes the growing fear of job crises. Will AI help or hinder our career opportunities? All though it’s hard to argue the fact that intelligent machines are in fact reliable when it comes to logical decision-making, there are still aspects of human intelligence that machines cannot mimic, like our emotional intelligence. Some argue that the combination of Human Intelligence and Artificial Intelligence will create more opportunities, not less.

“Machine Intelligence can help augment people to do their jobs by making them smarter in a situation, make better decisions, and offer greater engagement with customers.” – Charles Babcock: Editor at Information Week.

“HI is what defines us as humans and our relationship with everything on earth. Now, through the combination of HI and AI, we are at the brink of intelligence enhancement, which could be the most consequential technological development of our time, and in history.” – Bryan Johnson: Contributor at Techcrunch.

 

#4 – KEY TECHNOLOGIES

“The market for Artificial Intelligence (AI) technologies is flourishing. Beyond the hype and the heightened media attention, the numerous startups and the internet giants racing to acquire them, there is a significant increase in investment and adoption by enterprises.” – Gil Press: Managing Partner at gPress.

Australian startups such as Aipoly, creators of an app that combines image- recognition algorithms with smartphones to give instant feedback on surroundings for the visually impaired, have made a huge impact using Artificial Intelligence.

“People have told us that they’ve just started crying when they used it. They’ll say, ‘I have 200 apps on my phone and none of them have made the difference in my life that Aipoly has. It’s an amazing impact you can have on the life of someone that can’t see.” – Marita Cheng: Co-Founder of Aipoly.

There are a variety of AI tools and technologies taking the world by storm, among the most popular being deep learning platforms that provide algorithms such as FluidAI & MathWorks, biometrics for image and touch recognition like Affectiva and 3VR, and natural language processing tools used for fraud detection like Coveo and Sinequa.

 

For more resources, please see below:

The Business of Artificial Intelligence

Top 10 Hot Artificial Intelligence (AI) Technologies

These Emerging Technologies Will Play Critical Roles

Artificial Intelligence: Can It Replace Human Intelligence?

Data To Analytics To AI: From Descriptive To Predictive Analytics

How Big Data Is Empowering AI & Machine Learning At Scale

8 Ways Machine Learning Is Improving Companies’ Work Processes

Big Data & IoT Benefit From Machine Learning, AI Apocalypse Not Imminent

Meet The Australian Startup Using Artificial Intelligence To Help Blind People See

The Combination Of Human & Artificial Intelligence Will Define Humanity’s Future

Meet The Startups That Bring Artificial Intelligence To Log Management & Analysis

How Big Data Is Changing The Customer Experience & Improving SEO

The most powerful driver of success is a great customer experience, and almost every organisation is placing this at the core of of their strategy. But in order to provide excellence at every touchpoint of the customer journey, businesses must utilise data in the best way possible to understand their customers.

Digital innovation is accelerating our ability to do this at a great scale. Personalisation, optimisation and better-targeted campaigns are among the many benefits of insights derived from Big Data Analytics. But where do you start?

 

#1 – CROSS-CHANNEL ANALYTICS

“While volume, variety and velocity are good, value is always better.” – Experian.

The primary goal of digital marketers today is getting an ROI on their marketing efforts. Analysing the activity of customers across different channels, seeing which channels are performing better and how they work together can help you make the most out of your marketing budget. Finding golden pieces of information out of the mass volume of data your organisation has collected isn’t always easy. But digital marketers are finding tons of valuable data through the multi-channel funnel of google analytics, providing a single view of all the information needed to understand customer behaviour and measure performance.

“Cross-channel analytics seeks to provide insight into the path that the customer takes to conversion. This can take multiple forms; including understanding which channels combine to drive conversion, what popular paths are across and within channels, and finally detailed analysis of specific visitor paths.” – Matt Lawson: Managing Director of Ads Marketing at Google.

 

#2 – CUSTOMER DATA MANAGEMENT

“Businesses grapple with huge quantities and varieties of data on one hand, and ever-faster expectations for analysis on the other. The vendor community is responding by providing highly distributed architectures and new levels of memory and processing power.” – Doug Henschen: VP & Principal Analyst at Constellation research, Inc.

Data analytics tools help you collect, recover and categorise customer data according to profile, geolocation, purchase history and preferences in order to keep track of customer behaviour and target people more effectively.

“The social attributes of your customers is important if you want to deliver them highly satisfying experience for your business. Big Data can give valuable information regarding the social interactions of your customers, what their shopping preferences are and the kind of products they regularly need.” – Jason Bowden: Portfolio Manager of Enterprise Data Platforms at Cox Automotive Inc.

 

#3 – IMPROVING THE CUSTOMER JOURNEY

Are you frustrated by online shoppers who don’t make it past the first page of the checkout? You’re not the only one. There are many things you can do improve the online customer experience like good web design, helpful site search and making sure that navigating through your website is made as easy as possible.

Big Data Analytics helps us explore the best pathways to success/conversion. For example, analysing how your payment gateway optimises your customer experience.

“Customer psychology is enough of a minefield all by itself – you really don’t want to give them any additional reasons to abandon the cart.” – Shopify.

 

#4 – SEARCH ENGINE OPTIMISATION

“If you can’t measure it, you can’t improve it.” – Kissmetrics.

Using data science to get valuable insights into your website’s performance can answer a lot of your SEO questions so you can make better informed decisions and and be well on your way to higher keyword rankings and brand awareness. But the key with search engine optimisation is patience, as these results may not appear overnight. However, tracking our progress has become much easier with tools such as Tableau, BigQuery, Google Search Console and Google Analytics.

“The more information you possess, the better results you’ll see from your SEO strategies.” – Liza Perstneva: Corporate Speaker Coordinator at SEMrush.

 

#5 – DATA ACCURACY

“Improving the customer experience is the end game, but getting there requires more than data. It requires the right data, from multiple channels, integrated to give a holistic picture of the customer journey.” – Harvard Business Review.

In order to make decisions that are customer-centric, you need to ensure that the data you’re analysing is a true reflection of what’s really happening. Fortunately, popular cleansing tools like DataWrangler and OpenRefine can help your business generate more trustworthy insights, and even speed up information processing.

Going the extra mile when analysing your data pays off, and certain platforms like Apache Spark and Apache Hadoop can provide you with the efficient and accurate processing of data you’re looking for.

 

For more resources, please see below:

 

Cross-Channel Analytics:

Harnessing Big Data For Cross-Channel Success

Benefits Of Cross-Channel Analytics For Search Marketers

 

Improving The Customer Journey:

Marketing Analytics Can Improve The Customer Experience

 

Customer Data Management:

Journey To Customer Insight

Digital Marketing Optimisation

7 Ways To Effectively Manage Your Customer Data

5 Ways To Optimise Customer Experiences With Big Data

 

Search Engine Optimisation:

How Data Science Can Impact SEO

How Your Payment Gateway Impacts Your Customer Experience

Deliver an Excellent Customer Experience Using Big Data

4 Checkout Conversion Killers That May Drive Your Buyers Away

 

Data Accuracy:

How To Clean Your Data Quickly In Five Steps

Cyber Security Strengthened By Big Data Analytics & Machine Learning

Information is the most valuable asset, which is why everyone is recognising the importance of data in business and the economy. But our heavy reliance on information to make decisions requires an understanding of how to protect it.

With increasing data causing new cyber threats to surface daily, data practitioners who are utilising preventative technologies to bridge the security gap are at a competitive advantage when it comes to gaining the trust of their clients. Digital innovation enabled by data and analytics has taken the world by storm and is present in our everyday lives, even on our wrists. With wearable technology and mobile devices collecting a vast amount of information about us, it’s no surprise that security and privacy have become primary concerns.

“The sophistication, ferocity, and scope of attacks have also increased. We’ve moved beyond merely defending against criminals. We’re now fighting back against nation states, organised crime, and a troubling new trend: criminal organisations hacking on behalf of rogue nations.” – TechRepublic

To combat this threat, the use of analytics and machine learning are really adding value to businesses looking to build up their defences.

“Big Data and analytics is showing promise with improving cyber security. 90% of respondents from MeriTalk’s new U.S. government survey said they’ve seen a decline in security breaches.” – SentinelOne.

 

DETECTING & PREVENTING CYBER THREATS

“It’s data that’s getting stolen, but it’s also data that can come to the rescue. You just have to know how to use it in the right way.” – Susan O’Brien: Vice President of Marketing at Datameer.

According to the 2016 Big Data Cybersecurity Analytics Research Report, 72 percent of respondents said that Big Data Analytics played an important role in detecting advanced cyber threats.

Here’s some examples of how businesses can use Big Data Analytics to detect and prevent cyber attacks.

 

#1 – USING HISTORICAL DATA

With worldwide data reaching unprecedented levels, new cyber threats are emerging daily. To combat this, an article in CSO discusses the benefits of using historical data to identify potential cyber attacks while also predicting future events.

“Using this historical data, you can create statistical baselines to identify what is ‘normal’. You will then be able to determine when the data deviates from the norm. This historical data can also create new possibilities for predictive models, statistical models, and machine learning.”

 

#2 – MONITORING EMPLOYEE ACTIVITY

“Employing a system monitoring program where the HR person or compliance officer can replay the behavior of an insider is invaluable.” – Kevin Prince: CEO of StratoZen.

Frequent news headlines about “inside jobs” involving data hacks and leaking of information make it hard to ignore the fact that employee-related breaches are on the rise.

By ensuring that access to sensitive information is limited only to the relevant employees, and appropriate policies and procedures are put in place to protect and monitor the use of information, organisations can prevent security breaches by staff.

“Unauthorised access is when staffers use applications to view files or change data they should not be able to touch. This usually requires another employee, such as a system administrator, to be lax with system access controls. Data theft or destruction can follow.” – Justin Kapahi: Vice President of Solutions & Security at External IT.

 

#3 – EDUCATING YOUR TEAM

Although it’s crucial to take the right security measures, educating your team on how to recognise potential threats is just as important. Cyber criminals are targeting employees in many ways including text, email, phone calls, fake websites and dangerous links that could give hackers possession of an organisation’s most confidential information.

“Hackers routinely target workers who are dangerously oblivious to proper cybersecurity practices. Managers who care about protecting their clients, their firms and themselves must prioritize educating employees of all levels on how breaches occur.” – Tech Center.

 

#4 – DEPLOYING AN INTRUSION DETECTION SYSTEM

Data encryption, multi-factor authentication and firewalls are all common security measures, but another important precaution to take is deploying an Intrusion Detection System (IDS).

“IDS provides an umbrella to the network by monitoring all traffic on specific segments that may contain malicious traffic or have mal-intent. The sole function of a network-based IDS is to monitor the traffic of that network.” – TechTarget.

When deploying an Intrusion Detection System, It’s important to understand the requirements of your business in order to select the one most suitable one for the company’s infrastructure.

“Intrusion detection and prevention should be used for all mission-critical systems and systems that are accessible via the Internet, such as Web servers, e-mail systems, servers that house customer or employee data, active directory server, or other systems that are deemed mission critical.” – IT Business Edge.

 

For more resources, please see below:

8 Ways To Prevent Data Breaches

How Big Data Is Improving Cyber Security

Your Biggest Cyber Security Threat? Your Employees

Hacker Hunting: Combatting Cybercrooks With Big Data

Intrusion Detection System Deployment Recommendations

Challenges to Cyber Security & How Big Data Analytics Can Help

Big Data & Machine Learning: A Perfect Pair For Cyber Security?

Healthcare, Cybersecurity & Innovation In The Wearable Technology Market

Big Data Analytics Strengthen Cybersecurity Postures, Reveals Ponemon Institute Report