What’s in store for data analytics in 2015 and beyond

Future Gazing

Since the last couple of years, we have experienced revolutionary changes in the data analytics arena.  Big data became main stream and Data Scientist got termed as the sexiest job.  Data explosion has come with its own fair share of challenges and opportunities.  As the businesses are looking forward to monetize the data, they are grappling with finding suitable business use cases to leverage and execute on the new data platform.  Added to this is the trouble of finding skilled workforce to address the burgeoning demand.

Recent Alteryx research report has found that 72% of the business leaders are not satisfied with the speed at which insights are derived from data and nine out of ten dissatisfied stakeholders blame others on the inability to blend data from various data sources.

What to expect?

Segmentation of Vendors – Industry is fast gyrating towards three categories of vendors who are providing technologies that assist the data analytics life cycle viz. Data Platform providers like Cloudera, MapR, Hortonworks etc., Data Wranglers such as DataRPM, Tamr etc. and Guided Data Discovery providers like Alteryx, Datameer, Databricks etc.  Adding interesting twist to this mix is the new age big data visualization vendors like Platfora, Tableau etc.

It’s something of an irony if you find striking similarity to the data world where we used to live in until recently which was dominated by Oracle, DB2, MS SQL Server etc., as Data Storage providers, Informatica, Datastage, Abinitio etc., as ETL providers and Cognos, Business Objects etc., as the vendors for BI / visualization.

Few other distinct trends which we would emerge in days to come would be:

  • Machine Learning would become main stream
  • Deep learning could fast replace machine based learning technologies
  • Most of the predictive modeling and data science could become code-less or automated
  • Everyone would become data analyst or at least would be able to do sophisticated analysis through the power of these new found tool sets
  • Data blending would become main stream and rapidly get commoditized – a real threat to Big Data based analytics
  • Adoption of real time streaming and analytics would be higher – expect Apache Storm and Spark to be heard more often than before during your discussions
  • Signals based approach would become more prevalent than the atypical use case driven analytics approach where advanced analytics would be driven by a library of domain based signals.  We already see companies like Opera Solutions, Platfora, IBM’s Watson etc., taking lead in this space.
  • AI / VR could become an integral part of the strategy for the forward looking organizations
  • Graph databases would be increasingly used as the new destination repository for guided discovery / analytics
  • CIOs would have minimal say on the choice of analytics / tools / methodologies which would be driven by the business through the newly created roles like CDO (Chief Data / Digital Officers) or CAO (Chief Analytics Officers)

How many of these trends have you seen already kicking in?  Or have I missed out something more critical and significant?  What do you think?

Please share your thoughts.

Let’s ask bigger questions…

Image Credit – Morguefile

Why Microsoft could become a force to reckon with in Machine Learning

Microsoft has gotten into a great course correction since Satya Nadella took over as the CEO. In its effort to transform itself into a platform company per the vision of the new CEO, Microsoft has been truly taking some critical steps in the Big Data analytics space.  Since the launch of its Azure Machine Learning platform, Microsoft has been quietly focussing on building the foundational blocks and consolidating the Azure MLs adoption.  It’s easy drag, drop and predict approach on a cloud based Machine Learning platform has won a solid following.  It has also been helping developers to jump start Machine Learning through its Microsoft Virtual Academy led courses such as :

Microsoft has also recently made a couple of rather significant acquisitions to bolster its case further.  It’s acquisition of Equivio, a Text Analysis / Machine Learning based eDiscovery / compliance vendor whose main product is Zoom, a court approved machine learning platform.  The deal is stated to be around $200 Million.  Microsoft is reportedly planning to utilize Equivio’s machine learning technology to further improve its Office 365’s eDiscovery and information governance capabilities.  It would help quickly search and find relevant information from the unstructured data present in documents.

Yet another recent acquisition had been Revolution Analytics – a commercial software and services provider for R, the world’s most widely used programming language for statistical computing and predictive analytics.   It has also extended its support for open source communities by adopting Linux and also partnered with Hortonworks, a open source Hadoop distribution vendor to extend Big Data to the enterprise through its Azure HDInsight Big Data platform offering.  Microsoft had also open sourced its REEF to provide a big data analytics framework for YARN.

Microsoft is also facing off with IBM Watson through its ease of use Machine Learning approach.  It’s attacking IBM Watson’s biggest issue – the steep learning curve by providing an easy to use and adapt data model / APIs.  In its recent post, ZDNet reports that Microsoft’s goal for Azure Machine Learning is to develop data models that can be plugged directly into apps that will take that data, analyze and query it, and turn it into information that will be greater than the sum of its parts for a user.  Point in case its prebuilt data model for Microsoft Band which is its first fitness device.  The device monitored data is used for measuring, analyzing the health parameters.  It functions as a hub for data analysis of all the data collected through the device monitor.

Interesting times ahead for Microsoft since it seems to have placed its bets big on Analytics, Big Data, Cloud & Machine Learning in a big way.

Big Data : Four New Books

With the flurry of activities and the noise being created around Big Data, it is but natural to see huge content getting generated around the subject.

Not to be left behind, the Subject Matter Experts (SME) have brought in four books on Big Data – three from the SMEs and one from the vendor IBM.

You could find them at Amazon.  Check out the links below and let’s know your views.  Happy reading !!


Webinar : FICO Analytic Learning Series


FICO has announced the FICO Analytic Learning Webinar Series, five free webinars from October 2011 through January 2012 devoted to helping financial services analytics professionals improve their use of predictive analytics and modeling.

The webinars focus on sharing advanced analytic techniques pioneered by FICO experts along with case studies demonstrating how financial services institutions around the world are using analytics and modeling to solve business problems and achieve growth.

The first webinar in the series, “A Clear Diagnosis: Managing Predictive Models in a Highly Regulated, Dynamic Economy,” is scheduled for October 19. It focuses on best practices to build, improve, and refine methodologies for achieving regulatory compliance while simultaneously spurring growth. FICO is presenting the webinar twice, in order to focus separately on North American and European compliance issues.

Learn more about the Analytic Learning Webinar Series, read about other upcoming webinars in the series and register for one or more webinars in the series at:

North America: https://www.csvep.com/FICO/analytic.html
Europe/Asia/Africa: https://www.csvep.com/FICO/analytic_EMEA.html

BI and Analytics in Social Media

Social networking seems to be everywhere and even the BI tool vendors have recognized its importance by integrating social media based business intelligence and analytics in their offering spectrum.  Of late there has been a spurt of renewed interest in the analyst fraternity on social media based BI subsequent to the release of Tibco’s Silver Spotfire.   With Tibco’s support for S+ and R, users are expected to leverage Spotfire’s parametric driven analytic apps or its integrated predictive analytics features.

Most notable feature is the Spotfire Silver’s of a one year, no-cost, no-obligation to the cloud user with no IT involvement is sure to catch up the fancy of the fence sitters since it is being tuned to the cloud users.

Interesting areas being discussed and researched are :

  • Social BI Interactivity
  • Social BI Content Marts
  • Social BI Information Integration

Ability to extend real time customer support based on the customer feedbacks on the social media is being seen as an extension to CRM.  Dedicated customer support personnel are being tagged to trawl the social media for any references, good or bad, to the organization.  Latest example which is very relevant would be the amount of noise created in the social media on iPhone 4’s antenna related issues.  The pressure exerted by these social media has provided lots of negative publicity to otherwise Apple’s impeccable record.  Interesting aspect of such communication is that they are full-duplex, multi-point communications which is a classical case of flow of real-world intelligence.

Quite a few interesting conversations happening on this subject, few worth mentioning are :

By the way, does your organization has a strategy for the social media?  Happy to hear from you.

Webinar – Profit from Cognos BI: How can ISVs Benefit from IBM Cognos BI?

Better business decisions start with right information. when you need it, wherever you are. Though a growing number of organisation are beginning to recognize that business intelligence & analytics are critical enablers for success, huge amount of data still remains unutilized with their IT departments.

However, there is good news.  Even mid market & small sized businesses are now realizing this need and are looking out for intelligent solutions.

During this week’s “Thursdays with IBM” we will explore together on how IBM can help ISVs to add intelligence to their products. In the past we’ve noticed that ISVs who choose to leverage IBM Cognos are not just able to offer those critical & intelligent features but also boosts their bottom lines with better win rates & larger deals.

Join this Thursday at 4:00pm to know how can you turn your products intelligent.

Date : 29th July 2010
Speaker : Rajesh Shewani, Technical Sales Leader, Business Analytics, IBM India SA

Registration Link : https://indiawebinar.webex.com/indiawebinar/onstage/g.php?d=327421387&t=a