In May 2017 we unveiled our plans [https://techcommunity.microsoft.com/t5/SharePoint-Blog/Introducing-the-new-SharePoint-Admin-Center/b...] to simplify SharePoint administration through delivering an administrative experience that’s intuitive, intelligent, and simple.  Since then we’ve made available the new admin experience as Preview for customers who have enabled Targeted Release at the Tenant level.  In the next several weeks in our preview we’ll be introducing new updates on our journey to deliver an administrative console designed to help IT achieve more, so their users can achieve more.

New export capabilities allow you to export the displayed information in Site Management to CSV on both PC and Mac.  Using this output you can now use popular tools such as Microsoft Excel and PowerBI to simplify data prep, drive ad hoc analysis, and create dynamic charts and graphs.

In the upcoming updates you’ll now be able to customize views based on your individual preferences in addition to updating and customizing the default view of sites and related information.

NOTE Views you create are shared across all admins on the new SharePoint admin center.

If you have hundreds or even thousands of sites, they can be difficult to discover through a single view.  New search improvements will allow you to search across Site Management to find the right information when you need it whether searching by site name, Url, or the primary admin.

SharePoint was born on the concept of sharing and now we’re bringing that core principle to SharePoint admin center by enabling management of site level sharing settings for non-group-connected sites. We will follow this shortly with support for group-connected sites, and also support for advanced sharing settings. In case you're wondering, yes, we are working on a new tenant-level sharing page.

We’re also updating the email layout when contacting site administrators through the SharePoint admin center to make it cleaner and easier to read.

These updates will begin rolling out to Targeted Release in 4-8 weeks.

We're looking forward to the ongoing feedback. Use the feedback button at the bottom right of the new UI.  Also, if you see a survey that pops up and asks you how you feel about the new site, don't be shy, let us know. 

Manage sites in the new SharePoint admin center [https://support.office.com/en-us/article/manage-sites-in-the-new-sharepoint-admin-center-d8c63491-04...]

Machine learning, artificial intelligence, blockchains, predictive analytics – all amazing technologies which have promised to revolutionize business and society.

They are useless, however, without data. Fortunately for businesses and organizations which don’t have the resources to methodically collect every piece of useful information they will need themselves, a huge (and growing) amount is available freely online.

Two years ago I wrote an article listing 33 sources of Big Data availably for free online. Of course, in business technology terms that was a lifetime ago, so here’s an update with thirty new entries:

1. World Bank Open Data Datasets covering population demographics and a huge number of economic and development indicators from across the world.

2. IMF Data The International Monetary Fund publishes data on international finances, debt rates, foreign exchange reserves, commodity prices and investments.

3. The US National Center for Education Statistics Data on educational institutions and education demographics from the US and around the world.

4. The UK Data Centre The UK’s largest collection of social, economic and population data.

5 FiveThirtyEight A large number of polls providing data on public opinion of political and sporting issues.

6. FBI Uniform Crime Reporting The FBI is responsible for compiling and publishing national crime statistics, with free data available at national, state and county level.

7. Bureau of Justice Here you can find data on law enforcement agencies, jails, parole and probation agencies and courts.

8. Qlick Data Market Offers a free package with access to datasets covering world population, currencies, development indicators and weather data. 

9. NASA Exoplanet Archive Public datasets covering planets and stars gathered by NASA’s space exploration missions.

10. UN Comtrade Database Statistics compiled and published by the United Nations on international trade. Includes Comtrade Lab which is a showcase of how cutting edge analytics and tools are used to extract value from the data.

11. Financial Times Market Data Up to date information on financial markets from around the world, including stock price indexes, commodities and foreign exchange.

12. Google Trends Examine and analyze data on internet search activity and trending news stories around the world.

13. Twitter The advantage Twitter has over the others are that most conversations are public. This means that huge amounts of data is available through their API on who is talking about what, where, when and why.

14. Google Scholar Entire texts of academic papers, journals, books and legal case law.

15. Instagram As with Twitter, Instagram posts and conversations are public by default. Their APIs allow likes, mentions and business details to be analyzed.

16. OpenCorporates The world’s largest open database of companies.

17. Glassdoor API Information about job vacancies, candidates, salaries and employee satisfaction is available through their developer API.

18. IMDB Datasets Datasets in a number of formats drawn from the web’s largest resource on movies, television and people working in those industries.

19. OpenLibrary Data Dumps Datasets on books including catalogues from libraries around the world

20. Labelled Faces in the Wild 13,000 collated and labelled images of human faces, for use in developing applications involving facial recognition.

21. Microsoft Marco Microsoft’s open machine learning datasets for training systems in reading comprehension and question answering.

22. Machine Learning Dataset Repository Collection of open datasets contributed by data scientists involved in machine learning projects.

23. EBay Market Data Insights Data on millions of online sales and auctions from Ebay

24. Natural History Museum Data Portal Information on nearly 4 million historical specimens in the London museum’s collection, as well as scientific sound recordings of the natural world.

25. CERN Open Data More than one petabyte of data from particle physics experiments carried out by CERN.

26. One Million Audio Cover Images Dataset hosted at archive.org covering music released around the world, for use in image processing research

27. Complete Public Reddit Comments Corpus Over one billion public comments posted to Reddit between 2007 and 2015, for training language algorithms

28. Microsoft Azure Data Markets Free Datasets Freely available datasets covering everything from agriculture to weather

29. Irish Electric Vehicle Charge Point Status Collates data from the body which oversees the network of EV charge points across the Republic of Ireland and Northern Ireland.  

30. LondonAir Pollution and air quality data from across London

Ever wondered what is stopping you from landing an interview for a post in the Analytics Industry. Every person aspiring to get into the Analytics world has the same technical knowledge as you do. These ten non-technical books every aspiring Analytics candidate should read.

It is no doubt that Data is the new oil and more Data Analysts are going to be required to help make sense of the data. If you have decided to work in the analytics industry, you have taken the first step to this fantastic field. However, like you, many others want to grab the attention of Analytics recruiters.

An HR professional, unfortunately, shortlists your Resume. It means they will be scanning your profiles based on the Job Description provided by their Analytical teams.

Now you get where I am going?

Out efforts should not only make us stand out Analytical teams but also look lucrative for those people shortlisting your profiles. Keeping this in mind, I have worked on ten books every aspiring analytics candidate should read to fight the clutter.

Before you get into Analytics, you need have a strong reason. Recruiters can smell the desperation as soon as they lay their hands on your resume or when they first talk to you. Exactly why you need to have a strong reason to get into the Analytics world. It cannot be lame as following reasons.

"I want more money."

"It is a trending field."

or "I don't like my current field."

You need to get creative. Think from the recruiters perspective; they have probably heard the same reason from multiple people.

I have taken this test myself, and it has changed the way I look at my career. Once you have figured out, you are why you need to prepare your self for identifying your strengths. It is like doing to war; you would not go to the battlefield without knowing your key strengths.

Strengths Finder 2.0 helps you do just that. Prepare your mind and gives you the confidence to use your strengths while writing your resume. You can also provide a solid answer when recruiters ask about your strengths. It will boost your confidence during interviews.

I am yet to read this book, but I know the power of this book. It provides you knowledge about how small data can be informative and actionable. The human mind can comprehend such information easily which interesting to get results out of small data. Post-reading this book you can bring out interesting perspectives which many might not know.

Being in the Analytics field, it goes without saying that you need to know what Business Models exist and how you can tailor your analysis to fit the Business Model. Each report you create will only make sense if you can explain concerning how can to save cost, increase revenue, improve customer experience and showcase value proposition.

When moving into the Analytics industry, you will slowly find out that selling what work you did to other companies will become important. As much as you solve Business problems, you have to know yourself well. Also, you need to be clear about what tasks you can take up in this vast industry. In short, you cannot be generic. This book helps to understand yourself and portray your strengths in a magnified manner. You will be surprised to find many things you can say about yourself which you did not know earlier.

Every customer you are going to work with is going to expect you solve the Business problem you solve. However, to create a wow experience for them, you need to be able to spin up a story that helps your client more than what they have asked you to do. This way customers have a better brand recall when they work with you. If the clients are happy, then you are most likely set for a proper appraisal and eventually a promotion.

Not many will dare to read this book because of sheer laziness. However, if you can read just this book and apply most of the guides mentioned in this book, you will be significantly ahead of the clutter and find yourself confident. This book contains many ideas for the senior professional who want to make a shift in the Analytics Industry. Although this book is a generic book, all the principles apply to the Analytics industry.

Every session I interact with aspiring Analytics professional, I stress the importance of daily habits. Getting into the Analytics industry is not that easy by just learning theory. You need to practice daily. Imagine you are working for your first company, can you recall the amount of effort you put in to do the job well. Alternatively, did you just practice once you got the hang of it the next day?

Solving problems every day is the only way to increase your knowledge in this field. The more problems you solve, the better you get at critical thinking. The better you are you are at critical thinking, the better your confidence is boosted.

I have high respect for this book. After you have read this book, you will look at any Business from a different perspective. You will see at lag indicators and how leading indicators impact them. You will also find many flaws of vision to execution translation in many companies. Knowing how metrics are used to indicate progress makes you knowledgeable at the same time you will have difficulties explaining to people what metrics they should be considered to solve a problem.

I have not done my MBA, and I do not intend to one also. This book acts as a pivotal book for people who have not done an MBA and wanted to make a mark in the Analytics Industry. It contains most of what you need to know about a particular part of the company. It covers various topics such as Sales, Marketing, Human Resources, Finance and others as well. It is not a one time read book. In fact, you should keep referring to this book depending on which problem you are trying to solve for a client.

Seems like a daunting list?

It is not. To survive in the Analytics industry, you need to be a constant learner and have the ability to read through the enormous amount of whitepapers to solve a problem for your company. These books are non-technical, but they will warn you up and give you the perspective no other aspiring Analytics candidate will have. It will set you apart from all of them and increase your chances to land an interview and who know even get selected.