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

Five Big Data Skills That Will Help You Get Ahead In The Tech Industry

“The IT labor market is still very hot. The candidate is very much in the driver’s seat,” Jason Hayman: Market Research Manager at TEKsystems.

Businesses need confidence in their decision making process. Today, this means turning to the factual and reliable information derived from data. With many organisations looking to stay ahead of the competitive curve with techniques like data science and deep learning, this leaves a big window of opportunity for those with these in-demand skills.

If you’re a job seeker looking to up your analytics game, you may want to consider developing these skills:


#1 – HARNESS THE POWER OF BI TOOLS

“Today, tools such as Tableau and Power BI are a must to obtain business information in the correct desired form. This includes setting up the data source, data cleaning mechanism and analysis algorithms.” – Rhucha Kulkarni: Associate Features Editor at ReadITQuik.

Business Intelligence (BI) tools are applications, programs and software used to locate, analyse and document data. It is used to simplify the flow of data, making it more manageable. Access to accurate information in the right place and right form is a must-have for businesses looking to make the most of data in a reliable and time-effective way.

 

#2 – CONVERT KNOWLEDGE INTO ACTION

“Companies are trying to make sense of what the data can tell them about how to do business better. That, in turn, is fueling demand for people who can make sense of the information.” – Yuki Noguchi: Correspondent at NPR.

The ability to understand and utilise data to drive success can make you a big asset to an organisation. It’s not just about monitoring data, it’s about developing a solution strategy with the insights you’ve generated. Learning how to best utilise BI software can help you achieve this.

“This technology provides companies with actionable insights and greater visibility into their customers’ buying habits and trends so that they can always stay one step ahead of the competition.” – Paul Black: Data Marketing Magazine.

 

#3 – STAY AHEAD OF THE COMPETITION WITH PREDICTIVE ANALYSIS

“Today’s business applications are raking in mountains of new customer, market, social listening, and real-time app, cloud, or product performance data. Predictive analytics is one way to leverage all of that information, gain tangible new insights, and stay ahead of the competition.” – Rob Marvin: Assistant Editor at PC Mag.

The ability to use existing data to identify future risks and opportunities is an essential skill in the field of Data Analytics. Many industries like marketing, finance and healthcare can benefit from the forecasts created by statistical modeling, machine learning and other technologies.

“These techniques can provide managers and executives with decision-making tools to influence upselling, sales and revenue forecasting, manufacturing optimization, and even new product development.” – Georgetown University.

 

#4 – ENHANCE YOUR PROBLEM-SOLVING SKILLS

“Businesses face complex problems every day, and they are forced to solve them quickly and efficiently. That’s where decision science comes in. This market needs proven methodologies and frameworks to follow in order to materially affect business outcomes.” – Tom Pohlmann: Chief Marketing Officer at AHEAD.

A large part of of identifying challenges, risks and opportunities when analysing Big Data comes from implementing the right tools and frameworks to generate these insights. However, human intuition is still an important quality.

“We know executives pay attention to what data and analytic tells them, that’s the science part of the equation. But we also know they rely heavily on the art of intuition.” – Dan DiFilippo – Consulting Clients and Markets Leader For China and Hong Kong at PwC.

Intuition is the ability to understand something instinctively, without the need for conscious reasoning. In the era of of big data however, being unable to explain your logic when you come to a decision is a risk. In a survey conducted by PwC, 59% of decision makers said the analysis they require relies primarily on human judgment rather than machine algorithms.

“Seizing the opportunity will require leaders who can weigh the power and influence of both artificial and human intelligence, finding a balanced path that makes the most of each unique capability.” – Hugo Moreno: Contributor at Forbes.

 

#5 – BE VERSATILE

“In an age of Big Data, having tech skills is important, but the pendulum might be starting to swing the other way. More companies are requiring a mix of technology and people skills.” – Stephanie Vozza: Writer at Fast Company

The ability to take on multiple roles can make you more valuable to a team, not to mention give you a competitive advantage.

“Competition for analytical talent is extreme. And preserving and maintaining a base of talent within an organisation is difficult, particularly if you view this as a core competency.” – Ruben Sigala: Chief Analytics Officer at Caesars Entertainment.

In the field of data analytics, the combination of both hard skills (technical) and soft skills
(communication) is crucial to your success.

“Many who are working in the field today have more than one role in their job. They may act as researchers, who mine company data for information. They may also be involved with business management. Around 40% work in this capacity. Others work in creative and development roles.” – Ronald van Loon: Director of Advertisement.

“The right talent will go find the right technologies; the right talent will go solve the problems out there.” – Victor Nilson: Senior Vice President of Big Data at AT&T.

 

For more resources, please see below:

 

Data Analytics

Intuition Is The Antidote To Big Data

Pros and Cons Of Predictive Analysis

How Companies Are Using Data Analytics

Making Advanced Analytics Work For You

How Companies Are Using Big Data And Analytics

The Search For Data Analysts To Make Sense Of Big Data

Predictive Analytics, Big Data and How To Make Them Work For You

How Most Successful Companies Effectively Leverage Data & Analytics For Problem Solving

 

Data Tools

7 Top Tools For Taming Big Data

All The Best Big Data Tools and How To Use Them

Use Big Data To Get (And Stay) Ahead Of The Competition

Top 10 Tools For Working With Big Data For Successful Analytics Developers

 

Data Trends

10 Big Data Trends To Get Ahead of Now

Data Analytics Trends You Must Incorporate

 

Data Skills

The Hard And Soft Skills Of A Data Scientist

How To Boost Your Career In Big Data Analytics

August Insights On The Future of Big Data & Business Intelligence

Our reliance on data is growing, and the right alignment of IT and business objectives can help us find the answers we’re looking for. With the need to stay competitive by facilitating convenience and exceptional service to our customers, the importance of combining Big Data with business intelligence is a no-brainer.

 

BUSINESS INTELLIGENCE INCREASING ORGANISATIONAL SUCCESS

“BI’s primary objective is achieving better information visibility.” – Brad Cowdrey: Founder & CEO of Clear Peak LLC.

With the vast number of BI tools available, it’s easy to say that Business Intelligence makes our lives a whole lot easier, with the benefits of optimisation, simplified tasks, efficient workload management and even an increase in organisational success.

Businesses are achieving this by either embedding BI software in-house, buying embedding software or outsourcing their software development.

 

THE ALIGNMENT OF BIG DATA & BUSINESS INTELLIGENCE

“BI software has become almost a staple in any data-centric company regardless of size. Big or small, startup or well-rooted enterprise, the idea that data is power has finally begun to stick, and having quality tools to make this happen has become a business priority.” – Inside Big Data.

By collecting data from multiple, disparate systems, analysing and transforming it into meaningful insights and displaying it in an easy to understand format, businesses can utilise data to drive growth more rapidly than ever before.

“Australian organisations can now tap on a rather new concept to help drive business growth and competitive advantage. A combination of business intelligence software and collaboration tools has resulted in what many are calling collaborative business intelligence. Applied to company-wide analytics and reporting, collaborative business intelligence allows for better sharing of data and information and a more team approach to decision-making.” – Dr. Lawrence Ampofo: Founder & Director of Semantica Research.

 

HOW INNOVATION AND COLLABORATION WILL BE IMPACTED

“Every so often, we see a shift in technology that will be the catalyst for innovation. Today, SaaS, cloud computing, social computing and mobile computing are examples of popular new computing models that present an opportunity for innovation in business intelligence.” – Bob Zurek: Senior Vice President & Chief Technology Officer at HealthcareSource.

Cloud computing and data science enable discovery; and discovery leads to new products, services, applications and business models that change the way we do things. Although this presents a challenge to businesses who constantly need to evolve, the technologies we tap into are immensely useful in the process. They also act as an enabler between people and processes, streamlining the communication process and allowing for better collaboration. With devices simplifying the distribution of data flow, business leaders can make the right decisions in real-time.

“Data-driven businesses of the future will be able to tap on technologies and tools to allow peers to analyse data, and change information via the web. Collaboration business intelligence tools of the near future will allow teams to brainstorm ideas conveniently, remotely and seamlessly interact with each other using features like those on social networking websites.” – Wigins.

 

IMPLEMENTING BI AND BIG DATA INTO YOUR ORGANISATION

Business Intelligence is helping us seize opportunities and manage competitive threats, but getting it right is about much more than just building a data warehouse.

“You’ve got to have the right technology and a clear data architecture roadmap, but you’ve also got to have an organisation that can consume information and develop insight. That’s absolutely the number one tip: if you don’t view your BI project as a pervasive cultural approach to business, you might as well not bother starting.” – Martin Draper: Technology Director at Liberty.

Fostering the right culture can happen by educating your team, planning a long-term roadmap and having strategic clarity on what the desired outcome is.

“You need to define what success looks like, such as increasing customer value, increasing market penetration, or generating cost efficiencies. During this step, Big Data project owners should look to secure management buy-in. This will help ensure a strong data-driven culture pervades the organisation, giving projects legitimacy and value.” – David Sharp: CEO of RoZetta Technology.

 

For more resources, please see below:

The Future of Business Intelligence

The Difference Between Big Data & Business Intelligence

5 Ways The Internet of Things Will Change Global Security

How Building A Data Ecosystem Adds Value To Your Business

The Future of Business Intelligence Is Embedded and Conversational

CIO Strategies: Five Best Tips For Implementing Business Intelligence

Big Data And Cloud Computing: Innovation Opportunities and Challenges

Discovering New Innovations In Predictive Analytics And Business Intelligence

Six Reasons Why Data Visualisation Is The Future Of Storytelling

“A picture is worth a thousand words – especially when you are trying to find relationships and understand your data.” – SAS.

Gone are the days when businesses struggled to extract meaning from mass volumes of raw data and make insights come to light. Now, with the increasing number of data visualisation tools in the market, businesses are making faster and smarter decisions by engaging with data that’s easy to access and easy to understand.

Here’s 5 reasons why data visualisation is the future of storytelling.

 

#1- SIMPLICITY IS POWER

“Well designed data graphics are usually the simplest and at the same time, the most powerful.” – Centerline Digital.

Let’s say you’ve been given a short time frame to analyse thousands, or even millions of rows of numerical data, and make decisions based on the insights you’ve generated. How are you going to make it happen? Businesses have responded to this challenge by transforming data into visual content.

“Data visualisation turns numbers and letters into aesthetically pleasing visuals, making it easy to recognise patterns and find exceptions.” – Norman Shamas: Former Director of Curriculum at TechChange.

 

#2- CAPTURING ATTENTION

“The huge amounts of content available on the internet has significant implications for the modern day consumers’ attention span.” – Rob Weatherhead: The Guardian.

Speed, convenience and instant gratification enabled by technology are must-haves for today’s consumers. While trying to keep up with what’s in-demand, businesses have discovered the impact of visualising content in retaining engagement.

“Data visualisation excels in capturing a viewer’s attention and holding it through storytelling. It addresses a complex problem that could be easily looked over, and simplifies it using design.” – Elsa Wong: Author at Bridgeable.

 

#3 – SPEED & PRODUCTIVITY

“The faster a company can generate information from their sources, the faster they can generate their answers.” – Jessica Folliett: Author at Dataversy.

As the old saying goes, time is money. Many businesses struggle with the dilemma of whether or not to invest in Big Data due to the time and cost involved in generating insights. However, recent reports from Prysm Inc. show that data visualisation has significantly improved the decision making process when it comes to investing in data analytics.

“80 percent of organisations report more accurate decision making when using data visualisation tools. Further, 86 percent of companies report faster decision making through data visualisation, while 81 percent noted that the tools improved customer behavior insights.” – Prysm Inc.

 

#4 – UNDERSTANDING WHAT’S IMPORTANT

“The best data visualisations are ones that expose something new about the underlying patterns and relationships contained within the data. Understanding those relationships — and being able to observe them — is key to good decision making.” – Julie Steele: Author at O’Reilly.

Across many industries, data visualisation is being used to uncover hidden patterns and predict future trends and behaviors, helping businesses prepare for what’s to come.

“The primary objective of visual design is to present content to your readers in a manner that highlights what’s important, arranges it for clarity and leads them through it in a sequence that tells the story best.” – Stephen Few: Show Me The Numbers.

 

#5 – BREAKING THROUGH THE NOISE

“As we progress further into being an information society, data visualisation is becoming increasingly valuable.” – Elsa Wong: Author at Bridgeable.

In a world saturated with ever-increasing data and information, it’s now more important than ever for organisations to recognise what’s relevant and what isn’t. By combining data with creative visuals, businesses are able to find those golden nuggets of information amidst all the clutter.

“The beauty of data visualisation is that you can communicate far more information in a more digestible package than you can with text alone. While that doesn’t mean you have to use every piece of data at your disposal, you can tell a rich story in a single visualisation.” – Katy French: Author at Business 2 Community.

 

#6 – PERSUADING ACTION

“We’ve seen rapid growth in visualising as much data as possible to tell stories and present business results.” – Thomas Powell: CEO of ZingChart.

When done right, data visualisation tools can help you create engaging presentations that hold persuasive power with investors, managers and executives alike. Not only is visual data more engaging, it also helps you tell the strongest story and encourage a call-to-action.

“Unique and truly compelling visualisations are an underused, yet devastatingly effective tactic. They are equal parts rare and in demand.They are a catalyst for conversation, awareness, and action.” – Adam Singer: Author at ClickZ.

 

For more resources, please see below:

Storytelling With Data

Why Data Visualisation Matters

Why Data Visualisation Is Important

The Importance of Data Visualisation

Data Visualisation: What It Is And Why It Matters

Big Data Dilemma: Save Money Vs. Make Money

The Importance Of Big Data And Data Visualisation

How Time-To-Insight Is Driving Big Data Business Investment

7 Data-Storytelling Tips From Centuries-Old Data Visualisation

Data Visualisation: Your Secret Weapon In Storytelling and Persuasion

Say It Quick, Say It Well – The Attention Span Of A Modern Internet Consumer

Data Visualisation Holds The Key To More Efficient Decision-Making, New Report Reveals

The Increasing Importance of Data Visualisation: An Interview With ZingChart’s Thomas Powell

How To Make Big Data Work For Your Business In 6 Steps

“If you use bad quality data to make decisions, the insights will be meaningless.” – Florence La Carbona: Enterprise Data Manager at TAL.

Good data is good for business. You can have a vast amount it, and the technical experts to analyse it, but that still doesn’t mean you’ll get the answers you need.

Here’s how to make Big Data work for your business in 6 steps.


#1 – DEFINE YOUR PURPOSE

“Big Data can be a lot like spring cleaning. You can come across a lot of ‘stuff’ you don’t really need, but you still have to dig into it. So where do you start?” – TechRepublic.

In a world saturated with ever-increasing data and information, it’s important to recognise what’s relevant and what isn’t. The best way to do this is to make sure the data you’re using is aligned with the use case at hand.

“Good data quality always depends on the context in which it is used.” – bi-survey.com

Picking the right use case involves clearly defining your business outcomes. What are you trying to achieve with Big Data Analytics?

“The Business outcome will help the organisation stay focused on finding the right match for the business challenge. From there, they can clean and link only the most pertinent data.”- Yoni Malchi: Author at World Wide Technology.

 

#2 – IMPLEMENT THE RIGHT TOOLS

“Are ‘data-rich’ organisations really leveraging their data to support continuous improvement? To succeed at this they must provide user-friendly tools that turn what is often an overwhelming amount of data into actionable insights.” – Menno Veeneklaas & Tibor Schwartz: Partners In Performance.

Gone are the days where businesses struggled extract meaning from mass volumes of raw data and wait several days, even weeks, for results. New software tools have taken the pain out of the process involved in collecting and analysing data. Products like Hadoop, Pig, Hive and Spark allow you to create your own Big Data stack and build your own solution platform.

“New architectural concepts such as data lakes or technologies like Spark and Hadoop require enterprises to rethink their data pipelines, starting at the source where data is produced, to how it is transported and eventually stored and prepared for analysis.” – Kumar Srivastava: Contributor at TechCrunch.

 

#3 – BECOME A DATA DETECTIVE

“The more familiar you are with the data, the easier it is to spot something that seems strange. A good place to start is by looking at the raw data to see what jumps out.” – Matthew Peters: Research Scientist at Allen Institute of Artificial Intelligence.

Although it may seem like a dull task, taking the time to make sure you’re collecting the best data possible will give you a significant advantage when it comes to increasing your profitability and achieving your business goals.

“Working to make sure that your organisation has the most accurate data on its clients possible can seem quite tedious. However, software tools from providers make the process of collecting accurate data simple.” – Experian.

 

#4- KEEP TRACK OF YOUR PERFORMANCE

“Each key performance indicator should be defined to measure the quality, enhancement over time and ways in which to improve a specific set of data.” – Forbes.

The main purpose for implementing a Big Data Analytics strategy in any organisation is to see an improvement in performance by turning insights into solutions that drive competitive advantage.
It’s important to measure the performance of your data analytics project by measuring it against set objectives from its inception through to completion.

“Finding business intelligence in Big Data depends on identifying strong key performance indicators that deliver high value to the business.” – Mary Shacklett: Contributor at TechRepublic.

 

#5 – UNIFY YOUR DATA

“Demand is growing for analytics tools that seamlessly connect to and combine a wide variety of cloud-hosted data sources. Such tools enable businesses to explore and visualise any type of data stored anywhere, helping them discover hidden opportunity in their IoT investment.” – Tableau.

Data can tell you what you need to know, but only if you can see it clearly. By building a single source, 360-degree view of integrated data, your team can access and drive value from a cohesive analytic environment.

“A unified data architecture is a more comprehensive view of the overall enterprise architecture; a collection of services, platforms, applications, and tools that make the best use of available technologies to unleash the optimal value of data.” – tdwi.org.

 

#6 – START WITH PEOPLE, NOT TECHNOLOGY

“How do you harness the power of software-defined solutions, and how do you get yourself ready for the next phase of your business’ IT strategy?” – Logicalis.

Implementing Data Analytics doesn’t start with technology, it starts with people.

“How can the CIO and his team introduce big data into their workflow, and how can they translate what appears to be hieroglyphics to top-level executives in plain language?” – Aberdeen Essentials.

It all starts with knowledge. This involves de-mystifying the common buzz words around Big Data and Analytics, so that your team can communicate effectively about what you are trying to achieve. The second step is to approach Data Analytics in a way that’s relevant to your team.

“Ask questions about the pain points that people feel in their everyday jobs. This presents data analysis as the solution you know it can be, rather than the burden someone else may see it as. Approach your intent to get your office on board with data analysis as a way to make the team even stronger, and a way to empower each individual to do his or her job better, and to make better informed decisions.” – Kelli Simpson: Former Marketing Manager at DataHero.

 

For more resources, please see below:

Data Quality Importance

Unified Data Architecture

Top Ten Big Data Trends For 2017

From Big Data To Real-Time KPIs

Setting a KPI Course For Big Data

Big Data Project: Objectives First, Plan Second

How To Maintain A High-Quality Big Data Company

Nine Tips To Improve Data Quality & Improve Decisions

The Importance of Data Quality: Good, Bad, or Ugly

Getting Your Organisation To Embrace Big Data Analytics

Merging Key Performance Indicators With Big Data Analytics

For Analytics To Be The Answer, You Need The Right Use Cases

How To Measure The Success of Your Big Data & Analytics Strategy

Data Quality & Master Data Management: How To Improve Your Data Quality

“Big Data”, Business Intelligence (BI) and Key Performance Indicators (KPIs)

Five Tips For Data Efficiency

At Contexti, we’re always looking for new ways to make it easier to work with data.

When it comes to Big Data projects, it’s all about efficiency. We’ve rounded up the five best tips on how to make it happen.

 

#1 – DATA COMPRESSION

This can be a great way to reduce repetitive information, have shorter transition times and free up some storage space. The process of encoding data more efficiently to achieve a reduction in file size can happen in two ways: lossless and lossy compression.

“Lossless compression algorithms use statistic modeling techniques to reduce repetitive information in a file. Some of the methods may include removal of spacing characters, representing a string of repeated characters with a single character or replacing recurring characters with smaller bit sequences.” – Conrad Chung: Customer Service & Support Specialist at 2BrightSparks.

The great thing about lossless compression is that no data is lost during the compression process. With lossy compression, data such as multimedia files for images and music can be discarded. Lossy compression on the other hand, works very differently.

“These programs simply eliminate ‘unnecessary’ bits of information, tailoring the file so that it is smaller. This type of compression is used a lot for reducing the file size of bitmap pictures, which tend to be fairly bulky.” – Tom Harris: Contributing writer at HowStuffWorks.

 

#2 – CLOUD OPTIMISATION

“If your organisation wants to extract the highest level of application performance out of the computing platforms that it purchases, you should ensure that workloads are optimised for the hardware they run on.”- Joe Clabby: Contributor at TechTarget.

Choosing the right cloud services to achieve this requires consideration of efficiency, performance and cost advantage. A great tool for workload optimisation is the Cloudera Navigator Optimizer for Hadoop-based platforms.

“Cloudera Navigator Optimizer gives you the insights and risk-assessments you need to build out a comprehensive strategy for Hadoop success.” – Cloudera Inc.

Not only does it reduce risk and provide usage visibility, it’s also flexible and keeps up with changes in demand. “Simply upload your existing SQL workloads to get started, and Navigator Optimizer will identify relative risks and development costs for offloading these to Hadoop based on compatibility and complexity.”

 

#3 – UNIFIED STORAGE ARCHITECTURE

Many enterprises experience the same dilemma: unified storage system or traditional file/block storage system?

Randy Kerns, Senior Strategist & Analyst at Evaluator Group describes unified storage as “ A system that can do both block and file in the same system. It will meet the demands for applications that require block access, plus all of the file-based applications and typical user home directories you have.”

With the ability to simplify deployment and manage systems from multiple vendors, unified storage architecture is growing in popularity among storage administrators who are quickly seeing the benefits of the distributed access and centralised control it provides.

An article in TechTarget highlights the key benefits of running and managing files and applications from a single device: “One advantage of unified storage is reduced hardware requirements. Unified storage systems generally cost the same and enjoy the same level of reliability as dedicated file or block storage systems. Users can also benefit from advanced features such as storage snapshots and replication.”

 

#4 – DEDUPLICATION

“Deduplication is touted as one of the best ways to manage today’s explosive data growth.” – Brien Posey: Technology Author at TechRepublic.

Data deduplication is a technique of eliminating redundant or duplicate data in a data set and as a result, maximising storage savings and increasing the speed and efficiency at which data is processed.
By reducing the amount of storage space an organization needs to save its data, you’re not only saving time and money, but you’re preserving the integrity and security of of your data. “The simple truth is that to be effectively managed, adequately protected and completely recovered, your data size must be shrunk.” – Christophe Bertrand: VP of Product Marketing at Arcserve.

Here’s how it works: “Each chunk of data (e.g., a file, block or bits) is processed using a hash algorithm, generating a unique number for each piece. The resulting hash number is then compared to an index of other existing hash numbers. If that hash number is already in the index, the data does not need to be stored again. Otherwise, the new hash number is added to the index and the new data is stored.” – TechTarget.

 

#5 – CROSS-CHANNEL ANALYTICS

“Cross-channel analytics is a where multiple sets of data from different channels are linked together and analyzed in order to provide customer and marketing intelligence that the business can use. This can provide insights into which paths the customer takes to conversion or to actually buy the product or avail of the service. This then allows for proper and informed decision making to be made.” – Techopedia.

Among the many benefits of this process are understanding the impact of each channel, how they work together and determining which channel combinations get the highest results and conversions. It’s an efficient system that generates insights useful to each department within your organisation.

“Business leaders can use this information to design better process flows for customers by creating or revising customer journey maps. Meanwhile, marketers can use behavioral data from customer interactions in different channels for other purposes.” – TIBCO Blog.

 

For more resources, please see below:

 

Data Efficiency

What Are The Data Efficiency Technologies? – Performance: The Key To Data Efficiency

 

Data Compression

How File Compression Works

How Big Is Your Data, Really?

The Basic Principles of Data Compression

Data Compression: Advantages and Disadvantages

 

Cloud Optimisation

Cloudera Navigator Optimiser

Application Performance Tips: Workload Optimisation and Software Pathing

 

Unified Storage Architecture

Advantages of Using Unified Storage!

Unified Storage (Multiprotocol Storage)

Unified Storage Architecture Explained

Unified Storage Architecture: The Path To Reducing Long-Term Infrastructure Costs

 

Data Deduplication

What Is Data Deduplication?

How Data Deduplication Works

10 Things You Should Know About Data Deduplication

The ABCs Of Data Deduplication: Demystifying The Different Methods

Understanding Data Deduplication – And Why It’s Critical For Moving Data To The Cloud

 

Cross-Channel Analytics

What Is Cross-Channel Analytics?

Big Data Analytics: The Key To Understanding The Cross-Channel Customer

Hadoop Platforms Dominating The Market

“As a developer, understanding the Hadoop ecosystem can make you very valuable. Companies are leveraging it for more projects each day.” – Thomas Henson: Senior Software Engineer, Certified ScrumMaster & Technical Author at Pluralsight.

Over the past decade, the world has seen the launch of a multitude of ambitious frameworks and solutions aimed at tackling all your Big Data challenges, and we found which of the hadoop-integrated platforms were dominating the market.

 

#1 – CLOUDERA ENTERPRISE

The only platform with the native Hadoop Search engine. With high performance, low cost and advanced optimisation features, Cloudera Enterprise is among the most popular choices for enterprises who want fast, easy and secure Big Data projects.

“Cloudera supplements everything we liked about Hadoop by providing a clear path to being production-ready, ease of management, and top performance. We now have the agility to quickly react to new situations and deliver market-leading capabilities to our clients.” – CounterTack.

 

#2 – APACHE SPARK

Internet powerhouses like Netflix, Yahoo and eBay are loving Apache Spark, having deployed it at massive scale. Known for its speed, ease of use and generality, Apache Spark supports Scala, Python and Java and boasts speed 100-times faster than Hadoop for large-scale data processing.

“Spark … is what you might call a Swiss Army knife of Big Data analytics tools.” – Reynold Xin: Berkeley AmpLab Shark Development Lead.

 

#3 – APACHE HIVE

“Hive is the closest thing to a relational-database in the Hadoop ecosystem.” – Pluralsight.

Hive is data warehousing framework that allows for structuring and querying data using a language called HiveQL to write complex MapReduce over structured data in a distributed file system. Companies like Facebook, Qubole Inc. and Tata Consultancy Services are using this software to read, write and manage large datasets.

 

#4 – APACHE PIG

With big-time users like LinkedIn, Twitter and Salesforce, Apache Pig is popular for its ease of programming and customisation capabilities. It transforms large data sets with its own SQL-Like language. While applications like Hive are used for structured data, Pig is famous for transforming semi-structured and unstructured data, allowing developers to write complex MapReduce jobs without having to write them in Java.

 

#5 – APACHE SQOOP

“Not just a good general-purpose tool, but also a high-performance solution.” – Justin Kestelyn: Group Product Marketing Manager, Google Cloud Platform- Data Processing & Analytics.
Highly utilised for its efficiency and convenience, Sqoop allows developers to transfer data from a relational database into Hadoop, with significant opportunities for optimisation. Bundled with various connectors, it can be used for popular database and data warehousing systems such as such as Teradata, Netezza, Oracle, MySQL, Postgres, and HSQLDB.

 

#6 – APACHE ZOOKEEPER

The ultimate enabler of highly reliable distributed coordination in the Hadoop Ecosystem. ZooKeeper provides centralised services for configuration, synchronisation and group services.

“We use ZooKeeper extensively for discovery, resource allocation, leader election and high priority notifications. Our entire service is built up of multiple systems reading and writing to ZooKeeper.” – Konrad Beiske: Software Engineer at Elastic.co.

For more resources, please see the links below:

 

The Hadoop Ecosystem:

Big Data: 5 Major Advantages of Hadoop

Hadoop: The Ultimate List of Frameworks

20 Essential Hadoop Tools For Crunching Big Data

 

Cloudera Enterprise:

Cloudera Enterprise – Data Sheet

 

Apache Spark:

What Is Apache Spark?

Why All This Interest In Spark?

 

Apache Pig:

Apache Pig Overview

8 Reasons Why You Should Be Using Apache Pig

 

Apache Zookeeper:

Apache Zookeeper – The King of Coordination

 

Apache Sqoop:

Sqoop – The Apache Software Foundation!