Japanese Billionaire Celebrates Trump, Who Celebrates Him Back

President-elect Donald Trump, accompanied by SoftBank CEO Masayoshi Son, speaks to members of the media at Trump Tower in New York, Tuesday, Dec. 6, 2016. (AP Photo/Andrew Harnik)

Andrew Harnik / AP

The billionaire chief of Japanese technology giant SoftBank visited Donald Trump today, announcing that his companies would invest $50 billion in the United States and create 50,000 new jobs in the coming four years.

“I just came here to celebrate his new job,” Son told reporters camped out at Trump Tower. “He will do a lot of deregulation, I said, &;This is great, the U.S. will become great again.&039;”

“This is Masa of SoftBank from Japan,” Trump told reporters, with the Japanese executive cradled under his arm. “He&039;s one of the great men of industry, so I just want to thank you very much.”

Son told the Wall Street Journal the US investments would come from a $100 billion technology fund he has created in partnership with Saudi Arabia.

SoftBank already has a major presence in the US. It owns Sprint and recently acquired the UK-based chip designer ARM, whose chips are used throughout the mobile industry, including in the iPhone. The company is also an active venture capital investor in Silicon Valley, where it invested $1 billion in online lender SoFi last year (SoftBank is an investor in BuzzFeed).

There&039;s one particular US deal that is likely to be on Son&039;s mind. Since buying Sprint, he has pushed to merge the company with T-Mobile, in a takeover that would create a serious third competitor to AT&T and Verizon. A 2014 attempt to merge Sprint and T-Mobile was called off after federal regulators made it clear they would oppose the deal.

But Donald Trump will soon be appointing a new set of regulators, and Wall Street interpreted the friendly words with Son as a hint that a takeover attempt could be in the cards again. After Trump&039;s tweets, the T-Mobile&039;s stock price shot up by about 3%, bringing its valuation to just under $50 billion.

Google Finance

Quelle: <a href="Japanese Billionaire Celebrates Trump, Who Celebrates Him Back“>BuzzFeed

Snap Inc’s Current Hype Machine Could Hurt It Post-IPO

Snap Inc. is in the midst of a pre-IPO marketing push so masterful it will likely be taught in business schools for years to come. The company&;s unofficial roadshow kicked off with a product story in the Wall Street Journal introducing Spectacles, its new sunglass-with-a-camera product. The Spectacles announcement and limited rollout created a massive hype cycle, solidifying a narrative that Snap can do no wrong as it prepares to hit the public markets at an expected $25 billion valuation. But Snap will be valued based off ad sales not Spectacles sales and, with history as a guide, the hype may come back to bite it.

To see the sort of a disaster a much-hyped IPO can lead to for an emerging social company, you need only to look to Twitter’s November 2013 offering. Twitter, at the time, was still on a victory tour of its centrality to the 2012 election, and it did little to temper investor’s exuberant enthusiasm. On the day of Twitter’s IPO, then-Twitter CEO Dick Costolo told CNBC the company was experiencing “consistent, tremendous growth” and wanted to “enable the 2.3 billion connected people in the world to all become users of the platform.”

The consensus that Twitter was bound to continue growing users and revenue helped its stock rise 73% on its first day of trading, leaving it with a market cap of $24.4 billion by the end of the day — almost exactly where Snap is expected to start off. But the pressure to live up those lofty growth expectations became debilitating for Twitter relatively quickly, and it has spent almost the entire time since trying to explain why it has not met them. Three years later, Twitter has a market cap of $13 billion, about half of what it was worth on IPO day. After so much hype, its business never came close to matching Costolo’s predictions.

The parallels between Twitter and Snap are easy to miss if you&039;re enamored of Spectacles, but hard to dismiss once you look at the overall business. Snap, like Twitter, is an emerging social platform with significant cultural relevance but without the user numbers to match, thanks in part to a difficult-to-use product. Snapchat, like Twitter, appeals to a big but ultimately niche audience: Twitter appeals to newshounds, Snap to young people. And perhaps most importantly, Snap is bringing a largely unproven set of ad products to an online advertising game dominated by Google and Facebook; platforms that are so effective, advertisers told BuzzFeed News there’s a fat chance they’ll move large portions of their budgets anywhere else.

“The Twitter comparison is apt,” Kyle Bunch, of the ad agency R/GA, told BuzzFeed News. Bunch, who manages social platforms for the 2,000 person agency, said Twitter is in advertising plans for virtually all of R/GA’s clients, but Facebook and Google’s data and optimization capabilities have made spending money with them almost formulaic; X dollars in ads on those platforms gets you Y dollars in sales. Sure enough, 85 cents of every incremental ad dollar spent online is going to those two companies, according to Morgan Stanley analyst Brian Nowak. “It’s easy for advertisers to become essentially addicted to Facebook and Google and it’s really hard to cut back,” Bunch said.

All Sorts Of Challenges

Conversations with multiple advertisers revealed that Snap has a number of obstacles to overcome before it can be anything more than a fly for Google and Facebook to swat away.

Advertisers do not like the fact that Snap’s Snapchat ads are skippable. Though video ads on Snapchat can run for ten seconds, people actually watch them for an average of less than three, according to an Ad Age report that BuzzFeed News confirmed with multiple advertisers. When advertisers spend money, they are accustomed to force-feeding their messaging down consumers throats. Three seconds on Facebook isn’t even considered a view, and so three seconds on Snapchat is hard to work with.

Snapchat also exists largely as a black hole, where users go in and don&039;t come out via links like they do on Google, Facebook and even Twitter. Snapchat has made improvements to its ad platform in recent months, opening up an API to allow for better measurement, but it’s going to have difficulty attracting advertisers who need their ad spend to translate to web visits.

And then there’s the Facebook issue. Since Facebook cloned Snapchat Stories in Instagram, Snapchat Story views have gone down for brands, one ad pro told BuzzFeed News. Another agency executive said that Instagram Stories makes him doubt Snapchat can sustain its audience growth.

Because of these weaknesses, Snap has been unable to break out of the “experimental” portion of many advertisers’ budgets, according to the agency executive. These budgets, the agency executive said, get portioned out based on a 70/20/10 rule: 70% of advertiser budgets is spent inside platforms that are tried and true, 20% is spent with platforms that are still emerging and 10% in spent in the next/innovation bucket. “I would bet that most still put Snapchat in that 10%,” the agency executive said. “For us, Facebook is in that 70% and Snapchat is nowhere near that.”

Snap’s weaknesses have also made it entirely unappealing to other companies whose bread and butter is online advertising. Groupon, for instance, spends hundreds of millions of dollars a year on advertising but only a “tiny, tiny, tiny” amount of money on Snapchat, according to its CEO, Rich Williams. And Socialflow, a social platform that spends millions boosting content on social platforms, looked into Snapchat as a potential place to spend money, but it’s found no use for the platform so far. “There is a large barrier to entry to advertising on Snapchat,” Jess Bahr, director of paid social at Socialflow, told BuzzFeed News. “Unfortunately, it’s seen as risky and it’s hard to tie back to revenue.”

There’s Hope, But…

Snap will still pull in $935.5 million in revenue next year and $1,760.1 billion in 2018, according to the research firm eMarketer. Those numbers are still short of the more than $2 billion in revenue Twitter made last year, but eMarketer analyst Catherine Boyle said that its core product, Snapchat, is different than Twitter thanks to its high concentration of millennials, an attractive demographic to advertisers. “Snapchat will reach more than half of US millennials in 2016 and those millennials will make up 70% of Snapchat’s US user base in 2016,” Boyle said. “If, in a worse-case scenario, Snapchat does not expand its user base as we expect it will and it remains mostly a millennials platform, advertisers are likely to continue investing.”

Sarah Hofstetter, CEO of the ad agency 360i, said she likes what she’s seen from the company, giving Snap credit for improving its ad development and measurement in a “ridiculously short time.”

Still, asked what marketers talk about when it comes to Snap, Hofstetter said something likely familiar to executives at Twitter, who have been trying to make their product more usable for years. “Most marketers still today ask for a tutorial on it,” she said. “Their kids are on it but they don’t know how to use it.”

In one of business’s great contradictions, it’s possible to screw your company over through great marketing. Snap, ready to go public, may want to closely examine Twitter’s history of doing so or it could end up in the “tough lessons” section of the business textbooks as well.

Quelle: <a href="Snap Inc’s Current Hype Machine Could Hurt It Post-IPO“>BuzzFeed

Clustered Columnstore Index in Azure SQL Database

Columnstore index is the preferred technology to run analytics queries in Azure SQL Databases. We recently announced general availability if In-Memory technologies for all Premium databases. Similar to In-Memory OLTP, the columnstore index technology is not available in databases in the Standard and Basic pricing tiers today.

The columnstore technology is available in two flavors; clustered columnstore index (CCI) for DataMart analytics workloads and nonclustered columnstore index (NCCI) to run analytics queries on operational (i.e. OLTP) workload. Please refer to NCCI vs CCI for the differences between these two flavors of columnstore indexes. The columnstore index can speed up the performance of analytics queries up to 100x while significantly reducing the storage footprint. The data compression achieved depends on the schema and the data, but we see around 10x data compression on average when compared to rowstore with no compression. This blog will focus on Analytic workloads using CCI but cover NCCI in a future blog.

Clustered Columnstore index is available in Azure SQL Databases across all premium editions. However, it is not yet available on the Standard and Basic pricing tiers. Using this technology in Azure SQL Databases, you can lower the storage cost and getting a similar or better query performance on lower premium tiers.

The tables below show a typical analytics query with multi-table join running on P1 and P15 both with/without clustered columnstore index and storage savings achieved

Query Performance: Key point to note below is that with clustered columnstore index, the example query runs 5x faster on P1 compared to the same query running on P15 with rowstore with no tuning.  This can significantly lower the cost you need to pay to meet your workload requirements.

Pricing Tier
With Rowstore
With Columnstore
Performance Gains

P1
30.6 secs
4.2 secs
14x

P15
19.5 secs
0.319 secs
60x

Storage Size: The storage savings with columnstore compared to PAGE or NONE compressed tables shown below. While the cost of storage is already included with AzureDB, but lower storage can enable you to choose a lower tier. Note, this is generated test data so the compression is lower than what one would get for customer workloads.

Number of Rows
Size Rowstore (MB)
Size columnstore (MB)
Savings

3626191
212 (PAGE compression)
120
1.8x

3626191
756 (NONE compression)
120MB
6.2x

The best part of columnstore index technology is that it does not require any changes to your application. All you need to do is to either create or replace an existing index with columnstore index on your table(s).

How does Columnstore Index work?

As described earlier, the columnstore is just an index that stores data in a table as columns as shown below. The queries can continue to access the table requiring no changes.

Columnstore index delivers significant data compression and query performance due to the following three key factors

Reduced IO and Storage: Since data is stored as individual columns, it compresses really well as all values are drawn from the same domain (i.e. data type) and in many cases, the values repeat or are similar. The compression will depend on the data distribution but typical compression that we have seen is around 10x. This is significant because it enables you reduce the storage as the IO footprint of your database significantly.
Only Referenced columns need to be fetched: Most analytics queries fetch/process only a small set of columns. If you consider a typical Star Schema,  the FACT table is the one with most rows and it has large number of columns. With columnstore storage, SQL Server needs to fetch only the referenced columns unlike rowstore where the full row needs to be fetched regardless of number of columns referenced in the query. For example, consider a FACT table with 100 columns and an analytic query accessing this tables references only 5 columns. Now, by fetching only the referenced columns, you can potentially reduce IO by 95% with simplifying assumption that all columns take same storage. Note, this is on top of already 10x data compression provided by columnstore.
Efficient Data Processing: SQL Server has an industry leading query engine for columnstore data to deliver up to 100x speed up in query performance. For details, please refer to Data load into clustered columnstore index.

How do I create clustered columnstore index?

Creating a clustered columnstore index is like creating any other index. For example, I can create a regular rowstore table as follows

CREATE TABLE ACCOUNT (
ACCOUNTKEY INT NOT NULL,
ACCOUNTDESCRIPTION NVARCHAR (50),
ACCOUNTTYPE NVARCHAR (50),
ACCOUNTCODEALTERNATEKEY INT)

Any rows inserted into the table above are stored in rowstore format. Now, if you want to convert this table to store data in &;columnstore&039;, all you need to do is to execute the following SQL statement

CREATE CLUSTERED COLUMNSTORE index ACCOUNT_CI on ACCOUNT

If the rowstore table had a clustered BTREE index, then you can execute the following SQL Statement

CREATE CLUSTERED COLUMNSTORE index ACCOUNT_CI on ACCOUNT WITH (DROP_EXISTING = ON)

When and where should you use clustered columnstore Index?

Clustered Columnstore index primarily targets analytics workloads. The table below shows the common scenarios that have been successfully deployed with this technology.

Columnstore Option
Workload
Compression

CCI (clustered columnstore index)

Traditional DW workload with Star or Snowflake schema: Commonly you enable CCI on the FACT table but keep DIMENSION tables with rowstore with PAGE compression.
Additional Considerations: consider CCI for large dimension tables with > 1 million rows
Insert mostly workload: Many workloads such as IOT (Internet of things) insert large volume of data with minimal updates/deletes. These workloads can benefit with huge data compression as well as speed up of analytic queries.

10x on average

CCI/NCI (with one or more nonclustered indexes)

Similar to the ones mentioned with CCI but require (a) PK/FK enforcements (b) significant number of queries with equality predicate or short range queries. NCIs speed up the query performance by avoiding full table scans (c) update/delete deletes of rows which can be efficiently located using NCIs.

10X on average + additional storage for NCIs

Resources to get started

For more details, please refer to the following

Sample workload for columnstore index
Examples of production deployment of columnstore index
SQL Server Team&039;s blogs on columnstore index
MSDN documentation on columnstore index

Quelle: Azure

Supreme Court Sides With Samsung In Patent War With Apple

Jung Yeon-je / AFP / Getty Images

The Supreme Court on Tuesday ruled in favor of Samsung in a years-long patent battle pitting the Korean manufacturer against Apple over the value of design — specifically the design of the iPhone.

In a unanimous decision, the justices voted 8-0 to have the case resettled by a lower court, throwing out a $399 million judgment against Samsung for infringing on three of Apple&;s design patents for the iPhone.

Samsung was successful in convincing the court that it should not have to pay the full amount, which comes from the total profits Samsung banked from eleven of its phone models that mimicked the iPhone&039;s design. Instead, Samsung argued, the company should only pay for the value of the individual parts that it copied, not the entire value of the phone.

The Supreme court agreed, ruling that damages awarded in a design patent case can be based on individual components as well as the entire product. Rather than decide the exact dollar amount Samsung should owe, the justices sent the case back down to the lower court, giving Samsung another chance to argue for a smaller penalty.

Quelle: <a href="Supreme Court Sides With Samsung In Patent War With Apple“>BuzzFeed

Silicon Valley's Most Popular Forum Bans Stories About Politics

Earlier today the moderators on Hacker News, an influential online discussion forum run by Y Combinator, the startup incubator, announced that this will be “Political Detox Week” on the forum, and encouraged commenters to flag both political stories and political threads in non-political stories. “We&;ll kill such stories and threads when we see them,” wrote Daniel Gackle, head of community for Hacker News, who goes by the handle “dang” on the site.

In response to questions from BuzzFeed News, Gackle said the experiment in moderation was prompted by “an increase in accounts that have been using HN primarily for political purposes.”

In a post outlining the rules of Political Detox Week, Gackle wrote said this experiment was meant to honor Hacker News values of “intellectual curiosity and thoughtful conversation,” instead of the flame wars that happen “when political conflicts activate the primitive brain.”

When commenters asked about how the moderators intended to judge what was “political,” Gackle elaborated: “The main concern here is pure politics: the conflicts around party, ideology, nation, race, gender, class, and religion that get people hot and turn into flamewars on the internet.”

But many Hacker News community members objected to both the idea of censorship and the impulse to secede from politics, especially given the tech industry&039;s inextricable role in national debates over job loss and automation, the way that social media can amplify political propaganda, and the fact that Silicon Valley is stilllargely dominated by white male gatekeepers.

The most upvoted comment on the site, from a user who goes by the handle tarikjn, who found the experiment troubling:

I find this experiment a bit strange/disturbing, avoiding political subjects is a way of putting the head in the sand. HN is a community of hackers and entrepreneurs and politics affects these subjects one way or another wether we want to avoid it or not, and are an important component of entrepreneurial and technical subjects. It might be fine if HN was a scientific community, but it is not the case, and even then politics do interact with science, as one can conduct scientific experiments on government decisions, or politics can attack scientific community positions (e.g. climate change).

Hacker News was first launched by Y Combinator founder Paul Graham back in 2007 and still functions as the tech industry’s very own Reddit.

Y Combinator took a much different position on politics this year, when billionaire investor Peter Thiel, a part-time partner at YC, wanted to promote his views. In response to calls to cut ties with Thiel, who is now helping to run the transition team for President Elect Donald Trump, Sam Altman (president of Y Combinator&039;s parent company) wrote, “Diversity of opinion is painful but critical to the health of a democratic society.”

On Twitter, some commenters called bullshit on the idea of banishing the political as the best way to promote more thoughtful discussion:

Matthew Garrett, a security developer, pointed out that the detox diet silenced discussion around important topics, like a story about why diversity has stalled in major tech corporations:

Other Hacker News users, like commenter chrissnell, commended the experiment as an effort to promote objectivity.

I&039;d rather see HN go politics-free forever. Political discussions do not enjoy the same level of objectivity that technical and business discussions do. Frankly, it may be impossible to expect objectivity within political discussion because our political feelings are so deeply-held and tied to our individual upbringings, culture, and locale.

Another commenter, who goes by the handle ben0x539, noted that “racist, misogynist, fascist hackers” already feel safe on Hacker News, so this detox would end up marginalizing minority voices:

I feel like trying to ban discussion of these conflicts will lead to the same outcome that reddit&039;s weird “free speech” policy had, if more subtly. If Hacker News is the place where racist, misogynist, fascist hackers can feel particularly safe, that&039;s going to be the kind of people you attract, at the expense of marginalized hackers.

There is no neutral option around this kind of politics and I&039;ll be sad to see HN throw marginalized people under the bus to ensure the comfort of the privileged.

Danilo Campos, a software engineer who has been documenting abuse on Hacker News under for years, had little patience for forum members who argued that Political Detox Week was designed to keep out hate speech on the site:

When BuzzFeed asked Campos if Hacker News had ever responded to his campaign, Campos sent this interaction with Altman from 2014:

Here is the full text of the statement sent to BuzzFeed from Hacker News:

What prompted it was an increase in accounts that have been using HN primarily for political purposes. Politics are inextricably mixed with a lot of the topics that get discussed on the site, but it&039;s important that HN not turn into just another a political battlefield. We thought a one-week abstention from politics might be an interesting thing to try. Our hope is that it will help clarify what kind of site Hacker News is/isn&039;t. On HN, most flagging of stories is done by users, not moderators. For the purposes of this week, the idea is to flag all stories that are mostly political and to err on the side of flagging rather than not. But that&039;s just for this week. In general, we encourage users to err on the side of not flagging.

Quelle: <a href="Silicon Valley&039;s Most Popular Forum Bans Stories About Politics“>BuzzFeed

Facebook, Microsoft, Twitter And YouTube Team UP To Target Terrorist Content

Some of the biggest internet companies in the world are partnering to identify and remove terrorism-promoting content across their networks.

The companies — Facebook, Microsoft, Twitter and YouTube — will partner to share identifying information about terrorist content when they find it. Once a participating company identifies a terrorist video or image, it will pass along a hash — a sort of digital fingerprint that can be used to identify it on any platform, giving other participating companies an easy way to find and remove it themselves.

“Our companies will begin sharing hashes of the most extreme and egregious terrorist images and videos we have removed from our services — content most likely to violate all of our respective companies’ content policies,” the companies explained in a joint blog post. “Participating companies can then use those hashes to identify such content on their services, review against their respective policies and definitions, and remove matching content as appropriate.”

Similar partnership agreements around hash-sharing are being used to fight the spread of child porn.

The partnership does not mean content cited by one company will automatically be removed by others. “Content that violates one company&;s policies may not necessarily violate another&039;s,” one participating company said in an email.
“The hash-sharing provides a way for each company to more efficiently review content against its own independent policies.”

In recent years, terrorists have become skilled users of social media for recruitment and propaganda purposes. Twitter alone has suspended more than 360,000 accounts for making violent threats or promoting terrorism.

Many of the companies involved in this partnership own platforms that are essentially the modern day town squares; places that host easy to access public dialogues. Removing any content on these platforms is therefore a serious matter, as the companies note in their joint blog post.

“We are committed to protecting our users’ privacy and their ability to express themselves freely and safely on our platforms,” the blog post said. “We also seek to engage with the wider community of interested stakeholders in a transparent, thoughtful and responsible way as we further our shared objective to prevent the spread of terrorist content online while respecting human rights.”

Quelle: <a href="Facebook, Microsoft, Twitter And YouTube Team UP To Target Terrorist Content“>BuzzFeed

Uber Just Bought An AI Startup To Make Its Self-Driving Cars Smarter

An Uber car outfitted with self-driving technology in Pittsburgh, Pennsylvania.

Afp / AFP / Getty Images

Uber is doubling down on self-driving cars. The company said Monday that it has acquired an artificial intelligence startup called Geometric Intelligence and tapped the company&;s founders as co-directors of its new in-house AI research lab. Terms of the deal were not disclosed.

Dubbed Uber AI Labs, Uber’s new artificial intelligence research arm is intended to explore AI applications beyond self-driving car efforts, the company said in a blog post announcing the acquisition. Machine learning could improve routing algorithms, or the process of matching up riders for UberPool.

Geometric Intelligence&039;s approach to artificial intelligence is unique in that it focuses on developing AI that “learns” by extrapolating from a palette of rules, rather than crunching vast piles of data. Uber told The New York Times it found this “evolutionary” method of developing AI particularly compelling because it aims to mimic how the human mind learns.

Most members of the 15-person team, who are scattered at universities around the US, will move to San Francisco, where Uber is based, to form the AI unit’s “initial core.”

In September, Uber began a pilot program that allows passengers in Pittsburgh to hail self-driving cars, which carry both a safety driver (ready to take the wheel during emergencies) and a co-pilot (to monitor the car and its route on a laptop). The company entered the self-driving car race later than some other tech companies and automakers, but got a jumpstart by poaching about 40 researchers from Carnegie Mellon University’s robotics unit.

Speaking at Vanity Fair’s New Establishment Summit this past October, Uber CEO Travis Kalanick said the ridehail juggernaut is at the “very beginning stages of becoming a robotics company.” The acquisition of Geometric Intelligence, a 15-person artificial intelligence startup founded by three academics, nearly two years after the company opened up its Advanced Technologies Center in Pittsburgh, shows how that evolution has progressed.

Silicon Valley companies have recently been competing to hire AI researchers. Apple, for example, has in the past year acquired three AI companies, and brought on a director of artificial intelligence in October. Uber is now joining the recruitment rush.

Quelle: <a href="Uber Just Bought An AI Startup To Make Its Self-Driving Cars Smarter“>BuzzFeed

Secondary Indexes on Column Store accelerate SQL Data Warehouse look up queries

We are pleased to announce that Azure SQL Data Warehouse now supports the creation of secondary B-Tree indexes (also referred to as non-clustered indexes or NCI) on column store tables (also referred to as clustered column store indexes or CCI). Most analytic queries aggregate large amounts of data and are served well by scanning the column store segments directly. However, there is often a need to look for a ‘needle in a haystack’ which translates to a query that does a lookup of a single row or a small range of rows. Such look up queries can get orders of magnitude (even 1000x) improvement in response time and potentially run in sub-second if there is a B-Tree index on the filter column.

SQL Data Warehouse is your go-to SQL-based view across data, offering a fast, fully managed, petabyte-scale cloud solution. It is highly elastic, enabling you to provision and scale up to 60 times larger in seconds. You can scale compute and storage independently, allowing you to range from burst to archival scenarios, and pay based off what you&;re using instead of being locked into a confined bundle. Plus, SQL Data Warehouse offers the unique option to pause compute, giving you even more freedom to better manage your cloud costs.

Prior to the availability of secondary B-Tree indexes on column store tables, users could meet response time requirements for their point look up queries by duplicating column store data in a clustered B-Tree index. However, the duplication of data adds implementation complexity, storage cost as well as latency. Some of these users have now tried the new secondary indexes over column store and are delighted that they can get the same interactive response time without the data duplication.

How to Create a Secondary Index on a Column Store Table

This follows the same syntax as the generic Create Index Transact-SQL statements. A simple test on 1TB TPC-H data demonstrated that the query time for selecting orders for a given orderkey from lineitem went down from 41 seconds to under a second after a secondary index on orderkey was added. 

Best Practices for Using Secondary Indexes

Here are some guidelines to bear in mind when using secondary indexes on column store tables.

Use them for high cardinality columns that are used as filters in queries returning a small number of rows.
Don’t be heavy handed with secondary indexes as there is an overhead to maintaining them during loads. Best to limit to 1 or 2 secondary indexes per table.

Secondary indexes can be created on partitioned column store tables as well. However, as they are local to each distribution and partition, they cannot be used to implement UNIQUE constraint.

Next Steps

In this blog post we talked about benefits of the new functionality offered by secondary B-Tree indexes on column store tables. This is now available in all SQL Data Warehouse Azure regions worldwide. We encourage you to try it out if you have a use case for point lookups.

Learn More

Check out the many resources for learning more about SQL Data Warehouse, including:

What is Azure SQL Data Warehouse?
SQL Data Warehouse best practices
Video library
MSDN forum
Stack Overflow forum
Quelle: Azure