Bring Hadoop, Spark and SQL into one flexible, open analytics platform. Today, we are pleased to announce that IBM BigInsights® 4.2 is generally available. BigInsights 4.2 is built on IBM Open Platform (IOP), IBM’s big data platform with Apache Spark and Apache Hadoop. IOP offers the ideal combination of Apache components to support big data applications. The BigInsights 4.2 release puts the full range of analytics for Hadoop, Spark and SQL into the hands of advanced analytics and data science teams on a single platform. IBM has deep Hadoop expertise, and in the last year, has moved into a very strong Apache Spark leadership position … more
Just like in the story of Goldilocks … you may be looking for modern data warehousing that is “just right.” Your IT strategy may include cloud and you may like the simplicity and scalability benefits of cloud … yet some data and applications may need to stay on-premises for a variety of reasons. Traditional data warehouses provide essential analytics, yet they may not be right for new types of analytics, data born on the cloud, or simply cannot contain a growing workload of new requests. IBM dashDB Local is an open preview technology that is … more
IBM Fluid Query offers a wide range of capabilities to help your business adapt to a hybrid data architecture and more importantly it helps you bridge across “data silos” for deeper insights that leverage more data. Fluid Query is a standard entitlement included with the Netezza Platform Software suite for PureData for Analytics (formerly Netezza). Fluid Query release 1.7 is now available, and you can learn more about its features below … more
There’s a new kid on the block and it’s called SDE! This is a new term that stands for Software Defined Environment (SDE), and it is here to change the way we think about the world of application, integration and middleware – as well as data warehouses … Put simply, a Software Defined Environment (SDE) optimizes the entire computing infrastructure — compute, storage and network resources. An SDE can automatically tailor itself to meet the needs of the workload that must be executed … more
I admit, I love cars. And as a car enthusiast, I cannot imagine not having my own car. I use it every day, I rely on it. But I accept that other people may be different. For them, using a cab or car service might be the better choice. And then there are people who want full flexibility of maybe a sports car, a truck and other vehicle options.
What does all this have to do with IT and Data Warehousing? Well, at IBM, we think most of our clients have similar, diverse needs when it comes to their data warehouse environment. Depending on the use case at hand, one of several different data warehouse form factors may be better than the others for a particular analytics workload at that time. IBM offers a range of form factors for its data warehousing technology to help meet these needs …. more
Data warehousing architectures have evolved considerably over recent years. As businesses try to derive insight as the basis of value creation, ALL roles must participate by leveraging new insights. As a result, analytics needs are expanding, markets are transforming and new business models are being created. This ushers in increased requirements for self-service analytics, and software-defined environments based on Docker containers can help increase agility … more
The first Virtual Enzee webcast of 2016 is scheduled for January 29th! I will be updating this blog during 2016 so you have a handy resource to find out what sessions are upcoming and also listen to the replays on demand. The topic on January 29th is Accelerating Open-Source R with IBM PureData System for Analytics (Netezza) … more
Skills are always an essential consideration in technical careers and it is important for data warehousing professionals to expand their knowledge to handle the proliferation of data types and volumes in 2016 and beyond.
These are my “top 10” resource picks that you may want to explore. I am choosing these because of their popularity and also because they represent new technologies you may face in 2016 … more
Fluid Query was first released earlier this year and version 1.6 is now here! This is the third “agile” release of the year. As part of NPS software, it is available at no charge to existing PureData clients.
This capability enables you to query more data for deeper analytics from PureData System for Analytics. For example, you can query data in the PureData System together with IBM BigInsights or other Hadoop implementations; relational databses like DB2, dashDB, Oracle or others; and several generations of PureData System for Analytics … more
The IBM PureData Systems for Analytics team has just released a new set of enhancements over current software versions of Netezza Platform Software (NPS), INZA software and IBM Fluid Query technology. These include enhanced integration, security, real-time analytics for z Systems and usability features, all included in our latest software suite that has been posted on Fix Central. There will be something here for everyone, whether you are looking to increase security, gain more leverage with DB2 Analytics Accelerator for z/OS* … more
A quick reference guide to IBM Data Warehousing sessions for BLU Acceleration in-memory database, PureData System for Analytics and new IBM Fluid Query
IBM Insight is always educational and fun, and this year is no exception. Many IBM technical experts and IBM clients will be presenting on a range of topics. This is an excellent opportunity to learn more about IBM products you already use, as well as products and technologies that you don’t. Here is a summary view of some keynotes, breakout sessions and events to consider as you plan your schedule. I have included my “editor’s pick” sessions in boldface type … more
Many shops will migrate to a new PureData System for Analytics appliance, Powered by Netezza Technology, simply by copying old data structures into the new data warehouse appliance. They then point their BI tools at it and voila, a 10x performance boost just for moving the data. Life is good … As the weeks wear on, 5.1 seconds become 6, then 7, then 10 seconds. Nobody is really watching, because 10 seconds is a phenomenal turnaround compared to their prior system’s 10-minute turnaround.
But six months to a year down the line, when the query takes 30 seconds or longer to run, someone may raise a flag of concern. By this time, we’ve built many new applications on these data structures. Far-and-away more data has been added to its storage. In true Dilbert-esque terms, loading more data makes the system go slower. The better part about a PureData machine is that it has the power to address this by adhering to a few simple rules.
Much Like Thomas Jefferson’s commission to Lewis & Clark for their expeditions, Data Scientists are commissioned by the business to understand the landscape of information across their enterprise, map disparate data sources and identify valuable assets.
By leveraging an assortment of technologies and innovative thinking, Data Scientists utilize every tool possible to glean transformative insights. Now that we can offer a higher level of data access with the new IBM Fluid Query capability, Data Scientists and Business Analysts can partner up (just like Lewis and Clark) to explore data from across the enterprise and discover business insights from “Systems of Record” and “Systems of Engagement” … more
Since its announcement in March, 2015, IBM Fluid Query has opened the door to better business insights for IBM PureData System for Analytics clients. Our clients have wanted and needed accessibility across a wide variety of data stores including Apache Hadoop with its unstructured stores, which is one of the key reasons for the massive growth in data volumes. There is also valuable data in other types of stores including relational databases that are often “systems of record” and “systems of insight”. Plus, Apache Spark is entering the picture as an up-and-coming engine for real-time analytics and machine learning.
IBM is pleased to announce IBM Fluid Query 1.5 to provide seamless integration with these additional data stores—making it even easier to get deeper insights from even more data. more
Join us online for a live chat with the experts on the new Fluid Query 1.5 functionality. This new technology is part of the Netezza Platform Software (NPS) and it lets you query PureData Systems for Analytics stores together with Hadoop, Spark, and relational stores such as DB2, dashDB, Oracle and even other PureData warehouses to enable deeper insights. The chat will be held from 11AM to 12:00 PM ET on August 4th… more
How to get the most out of your PureData System for Analytics using Hadoop as a cost-efficient extension
Today’s requirements for collecting huge amounts of data are different from several years back when only relational databases satisfied the need for a system of record.
Now, new data formats need to be acquired, stored and processed in a convenient and flexible way. Customers need to integrate different systems and platforms to unify data access and acquisition without losing control and security … more
by Isaac Moreno Navarro
In my previous post, I introduced IBM DB2 Analytics Accelerator (Accelerator) and explained how it is capable of serving online analytical processing (OLAP) and online transaction processing (OLTP) queries at the same time. Now it is time to go into more detail and explain how it all works … more
by Rich Hughes
Learn how IBM PureData System for Analytics and IBM Cognos BI helped client AOK Niedersachsen, provide better policyholder services, while accelerating data queries by 100X compared to the previous system. They also decreased operational costs, and are now better able to make informed, fact -based decisions … more
by Isaac Moreno Navarro
With the advent of the data warehouse, the possibility of using the same infrastructure for online transaction processing (OLTP) as well as for online analytical processing (OLAP) has become a controversial subject. You will find that different database vendors have different points of view. IBM’s approach nwith DB2 Analytics Accelerator, together with DB2 for z/OS, is to form a self-managing, hybrid workload-optimized database management system that runs each query workload in the most efficient way … more
by Ralf Goetz
Initially, it seems like just a different sequence of the two characters “T” and “L”. But this difference often separates successful big data projects from failed ones. Why is that? And how can you avoid falling into the most common data management traps around mastering big data? Let’s examine this topic in more detail … more
IBM named a Leader in the Latest Gartner Magic Quadrant for Data Warehouse and Data Management Solutions for Analytics
by Dennis Duckworth
In the most recently released Magic Quadrant for Data Warehouse and Data Management Solutions for Analytics (Published 12 February 2015; Analysts: Mark A. Beyer, Roxane Edjali), Gartner placed IBM in the Leaders Quadrant.
If you are a follower of that particular Magic Quadrant, you will know that IBM has been listed as a leader every year back to the first one in 2007 … more
by James Kobielus
It’s good to know that some things remain constant in the ever-changing data warehousing (DW) market. One of those constants is IBM’s continued leadership in this segment … more
The need for operational analytics
Today, businesses across the world face challenges dealing with the increasing cost and complexity of IT, as they cope with the growing volume, velocity and diversity of information. However, organizations realize that they must capitalize on this information through the smart use of analytics to meet emerging challenges and uncover new business opportunities … more
by Andrey Vykhodtsev
In my previous two posts I covered the differences in architecture between IBM PureData System for Analytics and Oracle Database, as well as differences in SQL. (See below for links.) In this post, I am going to cover another important topic – additional structures that speed-up data access … more
by Andrey Vykhodtsev
In my previous blog post, I discussed architectural differences between Oracle databases and IBM PureData System for Analytics, powered by Netezza technology. In this post I would like to talk about differences in data types and SQL syntax. Even though both databases support very similar SQL language syntax, there are some things that are worth mentioning … more
by Andrey Vykhodtsev
One aspect of my job is helping people who want to switch from Oracle Database to IBM PureData System for Analytics. They always tend to ask similar questions, so I thought I’d put together some things that I always go through … more