Organizations are struggling to capture and interpret data that is spread across various analytic systems, each system handling different types of processing and data. The space to be the leader in big data analytics market and data warehouse is getting more crowded every day. The buzz words, B.I.G. data have taken new meaning as quants enter the market place as one of the top jobs. Today Teradata  talked to us about these 4 key market trends:

1. Driving towards specialized analytics engines

2. New user groups that want more scripting and procedural language support

3. The desire for simplicity of data integration through schema-on-read

4. Demand to operationalize big data insights accelerates need for performance.

What does this mean to you?

If you are able to use all the systems and integrate them, you would have a logical data warehouse with multiple systems, analytical techniques, programming languages and a diverse data types. This couldn’t be more important as I indicated in my report on Marketing Optimization paper.  It’s the age old problem of business users (CMOs) vs IT people who do care about the issues that Teradata spoke about. The key for any vendor is to understand what keeps the business user up at night and how to translate what the technical improvements make their day easier or the results they are measured on, better.

Essentially Marketers and other users of big data want to be about to run the right analytics on the right platform.  You also want the processing integrated. Often people want to use the data but not worry about where the data resides and they want easy access to data and analytics through existing tools. The point is to optimize, simply and orchestrate processing across and beyond the Teradata UDA.

Teradata has delivered three important innovative products to solidify Teradata’s position as a leader and pioneer in the data and  and again demonstrate their engineering prowess. What are those products?

1. Teradata QueryGrid™ - This is for a business user who wants to ask an important question and get a solid, reliable answer. The reason it would be interesting from an IT user is that there is no complex data movement and IT resources that need to be shuffled around and can reduce costly data duplication.

2. Teradata Database 15 - Teradata Database 15 provides support for Teradata QueryGrid. It enables the Teradata to be a single, seamless coordination point for users to have self-service access to data and analytics across multiple disparate systems. This means the delivery of a flexible schema-on-read so that companies can quickly adapt to change in source data and helps them to monetize the Internet interactions. What this means is that it empowers developers to interact with data using the tools and skills they already have. It also increases the high availability so that business have confidence in the data’s delivery.

3. Teradata Active EDW 6750 -  If you are using big data to make decisions you want it to be real-time so you make the best decision possible with the best data. Essentially B.I.G. needs to have B.I.G. performance. Teradata’s flagship platform is no even faster with a 40% performance increase, more Solid Date Drives (SSDs) for fast and consistent response times and more memory to power the Teradata intelligent Memory.
 
Active EDW 6750 claims to delivers unmatched power and space efficiency, setting the green, sustainability standard in data warehousing with 4X lower energy consumption and space utilization for the same performance system over just three years.Achieving a 40 percent increase in data warehouse processing performance, the Teradata Active EDW platform supports a big boost in business query rates. This is enabled by the balanced combination of the dual, powerful 12 Core Intel® Xeon® 2600 V2 processors and the performance-efficient NetApp E5500 data storage system. Key to effectively applying all this performance to user work is the Teradata Active System Management software that is now enhanced by the newest SUSE Linux operating system.
 
Teradata pioneered integration with Hadoop and HCatalog with Aster SQL-H to empower customers to run advanced analytics directly on vast amounts of data stored in Hadoop.  Now they are taking it to the next level with pushdown processing into Hadoop, leveraging the Hive performance improvements delivering results at unprecedented speed and scale.
 
If you use data, especially CMOs, Marketers, or Customer Experience  / Customer Service folks to better serve your customers you know that scale the breadth and sophistication of your data analytics to respond to the demands of business operations. The challenge is how to best orchestrate a wide variety of new analytic engines, file systems, storage techniques, procedural languages and data types into one cohesive, interconnected, and complementary analytic architecture. There is a big difference between the people who build and maintain store big data vs the people who use it. It’s often the issue most companies run into. It seems that Teradata is acknowledging the different users of data and adjusting their framework and technology to be able to make both parties.
 
As a business user of technology and big data, did this column help you understand the advancements in the technology? Or does it not really resonant to what you as a CMO or Customer experience person worry about?
@drnatalie
 
Skype: drnatalie007 | LinkedIn | Google+

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Business Research Themes

Data to Decisions, Marketing Transformation

Roles

Chief Information Officer, Chief Marketing Officer

Tags

Teradata, big data, analytics