Author: Pradeep Bhanot

Feed: Actian. Author: Pradeep Bhanot. Abraham Lincoln is quoted as saying, “If I had 8 hours to chop down a tree, I would spend 6 sharpening my axe.”  Spending 75% of the allotted time on preparation may seem like a lot, but in fact, most industry observers report that preparing data for business analysis or machine learning is indeed 70 to 80% of the time spent by data scientists and analysts.The data preparation pipeline consists of the following steps Access the data. Ingest (or Fetch) the data. Cleanse the data. Format the data. Combine the data. And finally, Analyze the ... Read More

Feed: Actian. Author: Pradeep Bhanot. The ISO 17788 Cloud Computing Overview and Vocabulary standard defines a hybrid cloud as “a cloud deployment model using at least two different cloud deployment models.”  When we talk about different deployment models, we are talking about private clouds, public clouds with multiple different cloud providers, and even legacy applications.  When the different deployment models are combined, the multi-hybrid cloud is created.  The multi-hybrid model allows businesses to optimize their operations.Competitive Advantage When a business employs a private and public cloud, they can make careful decisions regarding what applications and services are deployed to each ... Read More

Feed: Actian. Author: Pradeep Bhanot. This may seem like an academic question, but it is increasingly becoming a reality for modern businesses. What do you do when you have millions of records with infinite width and depth, and your data warehouse chokes?  Do you trim your data?  Do you add more infrastructure capacity?  Or do you need to look at a better data warehouse solution?This problem is akin to owning an old car that makes a bunch of noises, smells terrible, and has wheels that rattle when you drive down the road.  What do you do about it?  Drive slower ... Read More

Feed: Actian. Author: Pradeep Bhanot. A few months ago, companies went into crisis mode, globally – figuring out how to respond to the COVID-19 outbreak.  Since then, most organizations have overcome the initial shock and disruption and figured out how to adapt their workforce and business processes for a remote-work environment.  When this started, the hope was that COVID-19 would be a temporary disruption and would only last a few weeks or months.  It hasn’t played out that way – with the virus evolving into a global pandemic with no vaccine in sight; companies now realize that there is a ... Read More

Feed: Actian. Author: Pradeep Bhanot. When companies project data warehouse growth, they often look at a curve that mimic’s the growth of data in source systems.  This approach works if all you are concerned with is storage growth.  What is commonly overlooked is the compute growth curve for processing updates to your data.  As IT systems become more interconnected, data updates in one place have a ripple effect as they are replicated elsewhere.  Your data warehouse then receives updates from all impacted data sources, not just the place where the change was initiated.  If the compute growth isn’t planned for ... Read More

Feed: Actian. Author: Pradeep Bhanot. Enterprise Data Integration is the merging of data across two or more organizations.  This scenario is most commonly found when companies are going through mergers or acquisitions, and data from the two companies need to be brought together.  Other scenarios for Enterprise Data Integration are joint-partnerships (where two or more companies work together under the umbrella of a shared business entity) and integration across different business units with an enterprise conglomerate. In any of these scenarios, effective enterprise data integration requires a combination of organizational politics, effective data architecture, and scalable data integration techniques.This is ... Read More

Feed: Actian. Author: Pradeep Bhanot. The Vector for Hadoop offering from Actian delivers increased performance for analytic queries without the associated increase in cost.  If you are looking for high-performance analytics processing to drive operational decision making, where you do your processing matters.  By minimizing the movement of data and processing locally, you can drastically reduce latency.  By using a system like Actian Vector to perform that local processing, you can achieve even higher levels of performance.When people hear the statement “where you do your processing matters,” the first thought that comes to mind is network latency.  It’s easy to ... Read More

Feed: Actian. Author: Pradeep Bhanot. Have you ever tried to join your fact and dimension tables together to generate operational analytics? If you want to perform large scale data analysis on things like customer churn, you’re probably going to need to do this.  The problem is, these tables are very large, and when you bring them together, the resulting materialized data table is enormous (as in exponentially bigger than the source tables) and likely to time out before it ever completes.  If you can successfully pre-join the data together, the resulting data is probably out of date (sorry). This is ... Read More

Feed: Actian. Author: Pradeep Bhanot. In this second of a three-part blog series (part 1), we’ll explain how SQL execution in Actian Vector in Hadoop (VectorH) is much more functional and ready to run in an operational environment, and how the ability for VectorH to handle data updates efficiently can enable your production environment to stay current with the state of your business. In the first part of this three-part blog post, we showed the tremendous performance advantage VectorH has over other SQL on Hadoop alternatives. The third part will cover the advantages of the VectorH file format.Better SQL Functionality ... Read More

Feed: Actian. Author: Pradeep Bhanot. In this third and last part of the series on Actian Vector in Hadoop (VectorH), we will cover how the VectorH file format supports the performance and efficiency of our data analytics platform to accelerate business insights, as well as some of the other enterprise features that can help businesses move their Hadoop applications into production. Part one of this series showed the huge performance advantages VectorH has over other SQL on Hadoop alternatives, while part two explored the benefits of the richer implementation of SQL and the ability to perform data updates in VectorH.The ... Read More