Skip to main content

2019 Belongs to Modi

Those who think BJP has lost its support and people are unhappy might want to hear this.
“People who are making those comments are either middle class or short business class who were saving taxes. The tax component was their earning and now they have lost it. Now here comes data science. Picking data from rural India. How many families have benefited from the cooking gas and electricity? How many have got access to toilets and how many kids are going to school now? When I study this I am getting a figure of fifty crore. Even in forty-fifty crore, being a conservative I divide it by two, it is twenty crore. You know in 2014, the elections were won by a small margin of 1.4 crore and here you have a larger swing. So my calculation says 2019 belongs to Modi.

Comments

Post a Comment

Popular posts from this blog

Python and Parquet Performance

In Pandas, PyArrow, fastparquet, AWS Data Wrangler, PySpark and Dask. This post outlines how to use all common Python libraries to read and write Parquet format while taking advantage of  columnar storage ,  columnar compression  and  data partitioning . Used together, these three optimizations can dramatically accelerate I/O for your Python applications compared to CSV, JSON, HDF or other row-based formats. Parquet makes applications possible that are simply impossible using a text format like JSON or CSV. Introduction I have recently gotten more familiar with how to work with  Parquet  datasets across the six major tools used to read and write from Parquet in the Python ecosystem:  Pandas ,  PyArrow ,  fastparquet ,  AWS Data Wrangler ,  PySpark  and  Dask . My work of late in algorithmic trading involves switching between these tools a lot and as I said I often mix up the APIs. I use Pandas and PyArrow for in-RAM comput...
Post a Comment
Read more

Design of Large-Scale Services on Cloud Services PART 2

Decompose the Application by Workload Applications are typically composed of multiple workloads. Different workloads can, and often do, have different requirements, different levels of criticality to the business, and different levels of financial consideration associated with them. By decomposing an application into workloads, an organization provides itself with valuable flexibility. A workload-centric approach provides better controls over costs, more flexibility in choosing technologies best suited to the workload, workload specific approaches to availability and security, flexibility and agility in adding and deploying new capabilities, etc. Scenarios When thinking about resiliency, it’s sometimes helpful to do so in the context of scenarios. The following are examples of typical scenarios: Scenario 1 – Sports Data Service  A customer provides a data service that provides sports information. The service has two primary workloads. The first provides statistics for th...
Post a Comment
Read more

Cloud computing: Update

Cloud service contracts are still too complex for many businesses to grasp the potential risks and liabilities,  Businesses are buying into cloud services without fully understanding what they're paying for and what they can expect from the service. "One of the big barriers to using cloud computing is a lack of trust. I think you should be able to know what you're getting and what it means — and it should be easy to ensure that the terms in your contract are reasonable: open, transparent, safe and fair. Even if you don’t have a law degree," "Sensible, plain language contracts" be designed to spell out clear service level agreements and what a businesses' rights are on a range of issues, such as which third parties would be able to access a businesses' information or whether a firm will be notified in the event of data being stolen. Drawing up model contracts for cloud services is a "key pillar" of the  Cloud Computing strategy ....
Post a Comment
Read more