The Future of Big Data: 10 Predictions You Should Be Aware Of

Come 2020, every person in the world will be creating 7 MBs of data every second. We have already created more data in past couple of years than in the entire history of human kind. Big data has taken the world by storm and there are no signs of slowing down. You might be thinking, “Where would big data industry go from here?” Here are 10 big data predictions that will answer your intriguing question.

1. Machine Learning Will Be the Next Big Thing in Big Data

One of the hottest technology trends today is machine learning and it will play a big part in the future of big data as well. According to Ovum, Machine learning will be at the forefront of the big data revolution. It will help businesses in preparing data and conduct predictive analysis so that businesses can overcome future challenges easily.

2. Privacy Will Be the Biggest Challenge

Whether it is the internet of things or big data, the biggest challenge for emerging technologies has been security and privacy of data. The volume of data we are creating right now and the volume of data that will be created in the future will make privacy even more important as stakes will be much higher. According to Gartner, more than 50% of business ethics violation by 2018 will be data related. Data security and privacy concerns will be the biggest hurdle for big data industry and if it fails to cope with it in an effective manner, we will see a long list of technology trends that became a fad very quickly.

3. Chief Data Officer: A New Position Will Emerge

You might be familiar with Chief Executive Officer (CEO), Chief Marketing Officer (CMO) and Chief Information Officer (CIO) but have you ever heard about Chief Data Officer (CDO)? If your answer is no, do not worry because you will soon come to know about it. According to Forrester, we will see the emergence of chief data officer as the new position and businesses will appoint chief data officers. Although, the appointment of chief data officer solely depend on the type of business and its data needs but the wider adoption of big data technologies across enterprises, hiring a chief data officer will become the norm.

4. Data Scientists Will Be In High Demand

If you are still not quite sure about which career path to choose then, there is no better time to start your career in data sciences. As the volume of data grows and big data grows bigger, demand for data scientists, analysts and data management experts will shoot up.  The gap between the demand for data professionals and the availability will widen. This will help data scientists and analysts draw higher salaries. What are you waiting for? Dive into the world of data sciences and have a brighter future.

5. Businesses Will Buy Algorithms, Instead of Software

We will see a 360-degree shift in business approach towards software. More and more businesses will look to purchase algorithm instead of creating their own. After buying an algorithm, businesses can add their own data to it. It provides businesses with more customization options as compared to when they are buying software. You cannot tweak software according to your needs. In fact, it is the other way around. Your business will have to adjust according to the software processes but all this will end soon with algorithms selling services taking center stage.

6. Investments in Big Data Technologies Will Skyrocket

According to IDC analysts, “Total revenues from big data and business analytics will rise from $122 billion in 2015 to $187 billion in 2019.” Business spending on big data will surpass $57 billion dollars this year. Although, the business investments in big data might vary from industry to industry, the increase in big data spending will remain consistent overall.  Manufacturing industry will spend the most on big data technology while health care, banking, and resource industries will be the fastest to adopt.

7. More Developers Will Join the Big Data Revolution

According to statistics, there are six million developers currently working with big data and using advanced analytics. This makes up more than 33% of developers in the world. What’s even more amazing is that big data is just getting starting so will see a surge in a number of developer developing applications for big data in years to come. With the financial rewards in terms of higher salaries involved, developers will love to create applications that can play around with big data.

8. Prescriptive Analytics Will Become an Integral Part of BI Software

Gone are the days when businesses have to purchase dedicated software for everything. Today, businesses demand single software that provides all the features they need and software companies and giving them that. Business intelligence software is also following that trend and we will see prescriptive analysis capabilities added to this software in the future.

IDC predicts that half of the business analytics software will incorporate prescriptive analytics build on cognitive computing functionality. This will help businesses to make intelligent decisions at the right time. With intelligence built into the software, you can sift through large amounts of data quickly and get a competitive advantage over your competitors.

9. Big Data Will Help You Break Productivity Records

None of your future investments will deliver a higher return on your investment than if you invest in big data, especially when it comes to boosting your business productivity. To give you a better idea, let us put numbers into perspective. According to IDC, organizations that invest in this technology and attain capabilities to analyze large amounts of data quickly and extract actionable information can get an extra $430 billion in terms of productivity benefits over their competitors. Yes, you read that right, $430 billion dollars. Remember, actionable is the key word here. You need actionable information to take your productivity to new heights.

10. Big Data Will Be Replaced By Fast and Actionable Data

According to some big data experts, big data is dead. They argue that businesses do not even use a small portion of data they have access to and big does not always mean better. Sooner rather than later, big data will be replaced by fast and actionable data, which will help businesses, take the right decisions at the right time. Having tremendous amounts of data will not give you a competitive advantage over your competitors but how effectively and quickly you analyze the data and extract actionable information from it will.

The post The Future of Big Data: 10 Predictions You Should Be Aware Of appeared first on SmartData Collective.

Where is my next jobs in the age of Big Data and Automation

Where is my next jobs in the age of Big Data and Automation from Trieu Nguyen

Tài liệu hướng dẫn sử dụng Google Analytics

Đã từ lâu, Google Analytics đã đóng một vai trò quan trọng trong việc hỗ trợ quản lý các hoạt động của website và giúp các quản trị viên gia tăng hiệu quả hoạt động cho website của mình. Công cụ Analytics của Google cũng là một trong những công cụ hỗ trợ SEO rất tốt, cho phép chúng ta đo lường và gia tăng hiệu quả SEO.

Đã đến lúc chúng ta cần đưa công cụ này vào trong công việc SEO như là một trong những công cụ không thể thiếu cho tất cả các chiến dịch SEO. Để hỗ trợ bạn đọc trong việc sử dụng công cụ này một cách hiệu quả, vietmoz.net xin gửi đến bạn đọc tài liệu hướng dẫn tổng quan về cách sử dụng Google Analytics từ cơ bản đến nâng cao của tác giả Quang Huy – Bá Cường:

(Download tài liệu này tại đây)

Sau đây là một vài các ý chính có trong tài liệu này: 

1. Tổng quan về Google Analytics (Phần 1: Giá trị cốt lõi)
2. Hướng dẫn sử dụng giao diện Google Analytics (Phần 2: Giao diện cơ bản Google Analytics)
3. Một vài các tính năng nâng cao của Google Analytics (Phần 3: Google Analytics nâng cao)

1. Tổng quan về Google Analytics

Google Analytisc là một công cụ phân tích các dữ liệu của website miễn phí, được cung cấp bởi Google. Các dữ liệu này sẽ xoay quanh các hành vi của người dùng trước, trong và sau khi truy cập trang.

 

Từ những số liệu này, Google Analytics sẽ cho bạn một cái nhìn tổng quan về việc:

• Người dùng truy cập trang bằng cách nào
• Mức độ và loại tương tác của người dùng trên trang
• Cảm nhận của họ về nội dung trên trang
• Tại sao họ lại không thực hiện mua hàng trên trang
• Đối với các marketer, thì giải đáp được những câu hỏi này tức là bạn đã có thể biết được lý do tại sao tỷ lẹ chuyển đổi (conversion rate) thấp và cách gia tăng tỷ lệ này.

Những số liệu mà Google Analytics thu được bắt nguồn từ mã tracking code được cài đặt trên trang (mã bạn nhận được khi cài đặt Google Analytics).

Như vậy, những trang không có Analytics sẽ không thể gửi dữ liệu về server lưu trữ và xử lý số liệu của Google.

2. Hướng dẫn sử dụng giao diện Google Analytics

Để sử dụng thành thạo công cụ này trên Google Analytics, bạn cần nắm bắt được những thao tác cơ bản sau:

• thiết lập và tùy chỉnh các mốc thời gian
  
• đọc và tùy chỉnh các bảng số liệu của Google Analytics, lọc dữ liệu và thay đổi chế độ hiển thị của báo cáo trong Google Analytics như (bảng biểu, biểu đồ cột, tròn,..)

• phân tích luồng lưu lượng truy cập đến website
  

3. Một vài các tính năng nâng cao của Google Analytics

• Goal – mục tiêu: Công cụ 
  Để hỗ trợ các quản trị viên thiết lập và quản lý số các chuyển đổi trên trang, Google Analytics sử dụng công cụ Goal để tạo lập các mục tiêu trên trang, từ đó giúp các quản trị viên tính toán số chuyển đổi trên trang. (một chuyển đổi sẽ được xác nhận khi có một mục tiêu được hoàn thành bởi người dùng)
• Kênh:
  Giúp mô phỏng và quản lý chu trình hành vi của người dùng khi truy cập website (kênh mô phỏng phiều Marketing – Marketing Funnel)
  
  Đây là kênh mô phỏng phiều Marketing (Marketing Funnel). Đồng thời cung cấp cho người dùng các công cụ hỗ trợ để quản lý các hành vi của người dùng trong toàn bộ kênh, ngay từ khi người dùng mới chỉ là khách vào thăm cho đến khi họ trở thành khách hàng của website.

10 Best Ways to Learn Analytics Online

You know business analytics are crucial to the success of your organization. You know you need to improve your working BI knowledge.

But you don’t know where to start.

Don’t panic.

Here are our top ten (totally objective) picks for great online courses and resources to help you master the fundamentals of business analytics and take advantage of the tremendous opportunities better business intelligence can offer.

After all, access to easy learning is a key perk of the info revolution.

1. edX Data Analysis and Statistics Courses

edX brings you courses from leading universities all over the world — including Harvard, MIT, UC Berkeley, and more. Browse through until you find the course that best matches your needs. We recommend taking a close look at Statistical Thinking for Data Science, and Analytics taught by Andrew Gelman of the Statistical Inference, Causal Inference, and Social Science blog. It’s an excellent choice if you want to learn all about the role statistics plays in data science and analytics.

• Duration: Self-paced
• Fee: FREE
• Certificate: Yes; university credit also offered

2. National Tsing Hua University’s Business Analytics Using Forecasting via FutureLearn

This course is perfect for business users who want predictive analytics. If you frequently generate or read forecasts, this is the course for you. In this course, top professors teach you key predictive analytics strategies such as how to evaluate the performance of forecasting methods and how to tie forecasting analytics in with the business challenges.

• Duration: 6 weeks, 3 hours per week
• Fee: FREE
• Certificate: Yes

3. Codecademy’s Learn SQL

Codecademy is an absolute must for anyone with dreams of becoming a bona fide data analyst, and a major leg up for non-tech users who want to do more with data. SQL is the structured query language used by the vast majority of databases, CRMs, and business apps. Learn SQL and you’ll know how to access and read data in almost any context. This course is incredibly practical, prompting you to run your SQL commands via an interactive interface.

• Duration: Self-paced
• Fee: FREE
• Certificate: No

4. Big Data University’s Analytics, Big Data, and Data Science Courses

Tied in with UN Global Goals, Big Data University offers a ton of great data analytics learning content with an ethical edge. Choose from courses covering Big Data Fundamentals or go deeper with courses on Hadoop Programming and more. Big Data U is the best option for “unofficial” data scientists who are interested in making a career and a difference.

• Duration: Self-paced
• Fee: FREE
• Certificate: No

5. Occam’s Razor Blog, Podcast, and Videos

Not ready to commit to a full course? Author and data analytics pro, Avinash Kaushik’s blog brings you timely expert insights on what’s happening in data analytics, all within a business context. With insightful use cases and an eye to the future, even analysts can learn something new here.

• Duration: Self-paced
• Fee: FREE
• Certificate: No

6. Data Analysis Training and Tutorials from Lynda.com

As LinkedIn’s online learning platform, Lynda.com’s educational content is generated by practitioners, for practitioners. At the time of this post, there are 69 courses and 2,594 tutorials for data analysis training, covering a broad range of topics, including web analytics, data validation, how to use tools like Excel and SPSS Statistics, and much more. From data scientists to non-tech users, Lynda.com has something for everyone.

• Duration: Self-paced
• Fee: Free 10-day trial, $25 per month for basic membership, $37.50 for premium, flexible pricing options for teams of five or more
• Certificate: For select courses only

7. Wharton’s Business Analytics Specialization via Coursera

Learn and apply business data strategies in four targeted courses: Customer Analytics, Operations Analytics, People Analytics, and Accounting Analytics. The specialization culminates with a fifth course, the Business Analytics Capstone, a hands-on project that lets you apply your new data analysis skills to real problems faced by tech giants Yahoo, Google, and Facebook. The Capstone Project was designed in partnership with Yahoo with the goal of enabling the learner to make data-driven decisions in his or her organization.

Duration: 4 weeks per course, 1-6 hours per week, approximately 5-6 months total

Fee: 7-day free trial, then $49 per month

Certificate: Yes

8. Jigsaw Academy, The Online School of Analytics

Jigsaw Academy offers a well-curated collection of courses for new and seasoned data scientists, as well as non-tech beginners. You can choose a la carte classes to brush up on a particular topic, or opt for one of their extensive course packages which offer everything you need to know within a key area of analytics, such as Data Scientist, Big Data Analyst, or Machine Learning Specialist. Each course comes with a certificate upon completion.

Duration: 1 to 27 weeks depending on course

Fee: Courses start at $75

Certificate: Yes

9. The University of British Columbia’s Course on Creating and Managing the Analytical Business Culture

Our favorite thing about this course is that it deals with some of the trickiest real-world business intelligence problems, such as getting organizational buy-in and how to train and communicate with staff to create a business culture that embraces data-driven decision-making.

Duration: 4 weeks

Fee: $725-$740 CAD, special rate of $640 CAD available to members of the Digital Analytics Association

Certificate: This course can be applied to the UBC/DAA Award of Achievement in Digital Analytics or the Certificate in Web Intelligence

10. TM Forum’s Big Data Analytics Project

With over 85,000 members from 900+ global enterprises, TM Forum is one of the leading industry associations for digital business across industries. Their Big Data Analytics program covers best practices for extracting value from your business analytics and includes use cases to help you decide how to work through your business analytics challenges.

Duration: Self-paced

Fee: Corporate membership fees vary according to revenues but start at $1,700

Certificate: Yes

Now that you have ten great options to choose from, it’s time to get started! Whether you want to improve your skills or get a jumpstart to your learning, knowledge of BI will start transforming your professional career and organization (no matter the industry) fast. Take advantage of the info revolution and stay the course.