What’s Hot

IBM BigInsights version 4.2 is here!

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

IBM dashDB Local opens its preview for data warehousing on private clouds and 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 1.7 is here!

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

What you need to know: Software-Defined Environments (SDE) for data warehousing and 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

Hybrid data warehouse architecture: many choices for full flexibility

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

Using Docker containers for software-defined environments or private cloud implementations

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

Virtual Enzee webcast roundup for 2016

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

Build skills for 2016 and beyond: Data Warehousing & Analytics Top 10 Resources

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

What’s new: IBM Fluid Query 1.6 is here!

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

What’s new: Netezza Platform Software and INZA software for PureData Systems for Analytics

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

Get smart on IBM Data Warehousing at IBM Insight 2015

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

Performance – Getting There and Staying There with PureData System for Analytics

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.

Blaze your own trail, with deeper insights from more data!

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

IBM Fluid Query 1.5: Extending Insights Across More Data Stores

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 the Live Chat August 4th: Gain deeper insights using more data with IBM Fluid Query 1.5

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 4thmore

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

DB2 Analytics Accelerator: OLTP and OLAP in the same system at last! (part two)

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

Making the Insurance Policyholder Experience Better

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

IBM DB2 Analytics Accelerator: OLTP and OLAP in the same system at last!

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

What is the fundamental difference between “ETL” and “ELT” in the world of big data?

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

IBM’s Continued Leadership in the Data Warehousing Market

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

Getting started with IBM Fluid Query 1.0 for IBM PureData System for Analytics

by Doug Dailey

As Big Data concepts continue to mature and evolve, so does the technology that encourages its adoption. Enterprises are looking at ways to better leverage their data by reducing costs and positioning data for success based on its relevance. The yield for this exercise delivers optimum insights for the business at the right time.

Many are finding that Hadoop is not the answer for all of their data needs. They want to have access to various systems, rather than choosing a “one size fits all” mentality.  more

Making faster decisions at the point of engagement with IBM PureData System for Operational Analytics

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

Things you need to know when switching from Oracle database to Netezza (Part 3)

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

Things to know when switching from Oracle database to IBM PureData System for Analytics (Part 2)

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

Things to know when switching from Oracle Database to IBM PureData System for Analytics (Part 1)

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

 

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