2016年大数据发展趋势（BigData Trends 2016）

今天看到一篇大数据和云计算技术发展趋势预测的文章，本想翻译过来。但是，由于时间关系而没有翻译。后续补上，请谅解。

       原文：

BigData Trends 2016

The year 2015 was an important one in theworld of big data. What used to be hype became the norm as more businessesrealized that data, in all forms and sizes, is critical to making the bestpossible decisions. In 2016, we’ll see continued growth of systems that supportnon-relational or unstructured forms of data as well as massive volumes ofdata. These systems will evolve and mature to operate well inside of enterpriseIT systems and standards. This will enable both business users and datascientists to fully realize the value of big data. Each year at Tableau, westart a conversation about what’s happening in the industry. The discussiondrives our list of the top big-data trends for the following year. These areour predictions for 2016.

 

 

1.    The NoSQL Taskover

We noted the increasing adoption of NoSQLtechnologies, which are commonly associated with unstructured data, in lastyear’s version of Trends in Big Data. Going forward, the shift to NoSQL databasesbecoming a leading piece of the Enterprise IT Landscape becomes clear as thebenefits of schema-less database concepts become more pronounced. Nothing showsthe picture more starkly than looking at Gartner’s Magic Quadrant forOperational Database Management Systems which in the past was dominated byOracle, IBM, Microsoft and SAP. In contrast, in the most recent Magic Quadrant,we see the NoSQL companies, including MongoDB, DataStax, Redis Labs, MarkLogicand Amazon Web Services (with DynamoDB), outnumbering the traditional databasevendors in Gartner’s Leaders quadrant of the report.

Additional Reading:

Magic Quadrant for Operational DatabaseManagement Systems

 

2.    Apache Spark Lights Up Big Data

Apache Spark hasmoved from a being a component of the Hadoop ecosystem to the Big Data platformof choice for a number of enterprises. Spark provides dramatically

increased data processing speed compared toHadoop and is now the largest big data open source project, according to Sparkoriginator and Databricks co-founder,

Matei Zaharia. We see more and morecompelling enterprise use cases around Spark, such as at Goldman Sachs where Sparkhas become the “lingua franca” of big data analytics.

 

Additional Reading:

AtScale’sHadoop Maturity Survey highlights Big Data’s relentless growth

 

3.    Hadoop Project Mature

In a recentsurvey of 2,200 Hadoop customers, only 3% of respondents anticipate they willbe doing less with Hadoop in the next 12 months. 76% of those who already

use Hadoop plan on doing more within thenext 3 months and finally, almost half of the companies that haven’t deployedHadoop say they will within the next 12 months.

The same survey also found Tableau to bethe leading BI tool for companies using or planning to use Hadoop, as well asthose furthest along in Hadoop maturity.

       Enterprisescontinue their move from Hadoop Proof of Concepts to Production.

Additional Reading:

AtScale’sHadoop Maturity Survey highlights Big Data’s relentless growth

 

4.    Big Data Grows Up

As furtherevidence to the growing trend of Hadoop becoming a core part of the enterpriseIT landscape, we’ll see investment grow in the components surrounding

enterprise systems such as security. ApacheSentry project provides a system for enforcing fine-grained, role basedauthorization to data and metadata stored

on a Hadoop cluster. These are the types ofcapabilities that customers expect from their enterprise-grade RDBMS platformsand are now coming to the forefront of the

emerging big data technologies, thuseliminating one more barrier to enterprise adoption.

 

5.    Big Data Get Fast

With Hadoopgaining more traction in the enterprise, we see a growing demand from end usersfor the same fast data exploration capabilities they’ve come to expect

from traditional data warehouses. To meetthat end user demand, we see growing adoption of technologies such as ClouderaImpala, AtScale, Actian Vector and Jethro Data that enable the business user’sold friend, the OLAP cube, for Hadoop – further blurring the lines behind the “traditional” BI concepts and the world of “Big Data”.

 

 

6.    More Options For End Users

Self-service data preparation tools areexploding in popularity. This is in part due to the shift towardbusinessuser-generated data discovery tools such as Tableau that

reduce time to analyze data. Business usersalso want to be able to reduce the time and complexity of preparing data foranalysis, something that is especially important in

the world of big data when dealing with avariety of data types and formats. We’ve seen a host of innovation in this spacefrom companies focused on end user data

preparation for Big Data such as Alteryx,Trifacta, Paxata and Lavastorm while even seeing long established ETL leaderssuch as Informatica with their Rev product make

heavy investments here.

 

7.    In The Cloud

The “death” of the data warehouse has beenoverhyped for some time now, but it’s no secret that growth in this segment ofthe market has been slowing. But we now see a major shift in the application ofthis technology to the cloud where Amazon led the way with an on-demand clouddata warehouse in Redshift. Redshift was AWS’s fastest growing service but itnow has competition from Google with BigQuery,

offerings from long time data warehousepower players such as Microsoft (with Azure SQL Data Warehouse) and Teradata alongwith new start-ups such as Snowflake, winner of Strata + Hadoop World 2015Startup Showcase, also gaining adoption

in this space. Analysts cite 90% ofcompanies who have adopted Hadoop will also keep their data warehouses and withthese new cloud offerings, those customers can dynamically scale up or down theamount of storage and compute resources in the data warehouse relative to thelarger amounts of information stored in their Hadoop data lake.

Cloud Data Warehouse Race Heats Up

http://www.zdnet.com/article/cloud-data-warehouse-race-heats-up/

 

8.    IoT, Cloud and Big Data Come Together

The technologyis still in its early days, but the data from devices in the Internet of Thingswill become one of the “killer apps”for the cloud and a driver of petabyte scale data explosion. For this reason,we see leading cloud and data companies such as Google, Amazon Web Services andMicrosoft bringing Internet of Things services to life where the data can moveseamlessly to their cloud based analytics engines.

All the Things:Data Visualization in a World of Connected Devices

http://www.tableau.com/about/blog/2015/1/all-things-data-visualization-world-connected-devices-36393