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Big Data

Parallel ways of Data Scientist and Machine Learning




👉 📊 There are endless conversations, debates, and discussions over this popular topic, and it can be a little overwhelming to know where to start from data science experts to complete newbies.

🔥 While, from researchers to students, industry experts, and machine learning (ML) enthusiasts — keeping up with the best and the latest machine learning research is a matter of finding reliable information. Here in this blog, we are going to share information on how data science is evolving with the rising demand for Machine Learning.

Inside 🎰 Machine Learning- 👇

In amazingly simple words every time we pick our phones to get seek information from any search engine like google or any social media platform like Facebook or Instagram, Machine Learning is playing its role each moment. It is the role of Machine Learning to provide the most relevant information/ recommendations to the searcher. From searching for good restaurant hopping options to tips for skincare regime, we are contributing machine learning through our searches on the internet, without realizing it.

🎯 Machine Learning technology plays a big role in collecting and keeping track of user search behavioral data for the companies, so the same can be taken into consideration while taking the important product of services related decisions by Data Scientist or business personnel.

🗨 So, this was the explanation of how in our daily lives we are interacting with Machine learning Cluelessly. Now let us understand the role of data scientists and how it related to Machine Learning.

📉 Who is a Data Scientist?

🚀 This can be drafted as the one who is an expert in extracting meaningful information from the heaps of data. They are specialists, gathering, and analyzing large sets of structured and unstructured data. With a combination of computer science, statistics, and mathematics, Data scientists are analytical experts who utilize their skills both technologically and ethically to find trends and manage data. They analyze, process, and model data then translate the results to create actionable plans for companies and other organizations.

👩‍💻 The Sufficient knowledge of different Machine Learning techniques and like Python, SAS, R, and SQL/NoSQL database, and other tools Data Scientist can perform the task with very few challenges and easily outrank the competitor.

🎰 Machine Learning for Data Scientist or Vise-Versa? 👇

Taking into consideration the role of Data Scientist discussed above- without data, machine learning does not fulfill its use. This is how machine learning and data science go hand in hand as they both are incomplete without each other.

🗨 Where machine learning collects the data for Data scientists to evaluate and extract the meaningful out of it. With the increased use of technology/internet, the use of ML acts as a spur to push data science in high demand.

In the world of 📈 data science one can never feel the shortage of tools and algorithms to be applied to data, with this we can say data science skills also involves the ability to evaluate Machine learning and can make the machine as smart as to make their analyses process easier. Going forward, essential levels of machine learning will become a benchmark for data scientists. 🔻

Seeing from a different perspective, to match human abilities, machines need to be smart enough and Machine Learning is the soul of Artificial intelligence.

👨‍⚖️ Data Scientists must understand Machine Learning for the best outcomes and quality results. This can help machines to make the right decisions and smarter actions in real-time with zero human intervention. Hence, Data Scientists must acquire skills in Machine Learning. 👇


📖 Conclusion-

In the world of Data Science, Machine learning has already proven its worth, it is turning out to be the best solution to a deeper analysis of a huge amount of data. Data scientists must acquire knowledge of ML to standout in the competitive market.

✍ Author Bio :⤵

Senior Data Scientist and Alumnus of IIM- C (Indian Institute of Management – Kolkata) with over 25 years of professional experience Specialized in Data Science, Artificial Intelligence, and Machine Learning.
PMP Certified
ITIL Expert certified APMG, PEOPLECERT, and EXIN Accredited Trainer for all modules of ITIL till Expert Trained over 3000+ professionals across the globe currently authoring a book on ITIL “ITIL MADE EASY”.

Conducted myriad Project management and ITIL Process consulting engagements in various organizations. Performed maturity assessment, gap analysis, and Project management process definition and end to end implementation of Project management best practices. 👇

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Big Data

Certifications To Drive Your Big Data Professional Career




In the modern age, one of the most valuable assets a business possesses is the data it generates. Business data is an unparalleled source to derive a competitive advantage over other businesses operating within your niche or industry segment. It is so valuable, that businesses spend billions each year on data security and privacy measures, both to protect their customers as well as the valuable data itself.
However, raw data in itself does not offer much value. Given the large volumes of data that businesses produce on a daily basis, simply managing it can be a huge task, let alone analyzing it to draw the correct conclusions. This is where big data professionals come in.


How to Become a Certified Big Data Professional?

The larger a business is, the more data it likely generates. For enterprise-level businesses, this data can become so extensive that simple inference tools aren’t enough to draw valuable information from it. The vast quantities of data are full of hidden trends, process efficiency indicators, sales volume fluctuation, and even customer behavior. However, for an average-Joe, it may be virtually impossible to use it in a significant way. After all, it’s not as simple as figuring out how to get Spectrum TV.

But a certified big data professional has all the expertise and knowledge needed to make constructive use of the data that businesses accumulate. This is one of the reasons why data scientists are in such demand in the business world. Using sophisticated statistical and analytical techniques, big data professionals are able to correctly predict trends and identify areas of improvement. This helps businesses improve their overall process efficiency and position themselves to take advantage of emerging trends. If you’re thinking of dipping into the big data profession, here are a few certifications that will prove useful along the way:

1. Microsoft MCSE Data Management and Analytics.

2. Cloudera Data Professional Certification

3. Hortonworks Hadoop

4. EMC Data Science and Big Data Analytics

Here’s how these certifications can help you get closer to your goal of becoming a successful big data professional.


Microsoft MCSE Data Management and Analytics

Microsoft is one of the oldest and most iconic tech companies in modern history. So it makes sense that they have developed specialized tools and certifications to help professionals who work with big data in a business setting. The company’s MCSE program is designed to help individuals become proficient at using various Microsoft tools and software. Successfully completing the program means you become a certified big data professional in terms of:

  • SQL database administration.
  • Development
  • Machine learning.
  • Business intelligence reporting.

The program hones your skills so you can have demonstrable expertise in SQL, building data solutions for large-scale enterprises, and deriving intelligence from business data. Any tech-savvy employer will jump at the chance to add you to their team.


Cloudera Data Professional Certification

If you want to learn how to create and work on big data pipelines, the Cloudera certification is something you should seriously consider. The company has established itself as an authority on Hadoop, and getting certified by it is one of the most useful endorsements you can have in the big data profession. It lists a range of certifications that offer proficiency in Apache Spark, Hadoop Development, and Hadoop Administration.

Hortonworks Hadoop

Speaking of authorities in the Hadoop domain, Hortonworks is a commercial vendor that has been offering customized Hadoop tools and solutions to enterprises for some time now. These services have a broad range of applications in data management and intelligence. The company now also offers various certifications for Hadoop, including Hadoop development and administration as well as Spark development among others. The certification is great for building your skillset in:

  • Data ingestion.
  • Data transformation.
  • Analyzing big data.


EMC Data Science and Big Data Analytics

EMC offers certifications designed to build and increase proficiency in various specific aspects of the Hadoop environment. It covers a variety of bases, including Pig, Hive, and HBase. It also pays a lot of attention to delivering knowledge on data visualization, NLP, and even logistic regression. In addition, the certification will grant you proficiency in data analytics, data science roles, building complex data models, and evaluating it for results.

Big data professionals are needed by virtually every enterprise-level firm in the world. They are needed to analyze complex information, from measuring customer satisfaction ratios on the Spectrum cable phone number to identifying process inefficiencies in manufacturing. With an increased dependency on data to outperform and outclass the competition, businesses are willing to pay handsomely for this niche skillset. A professional certification can greatly increase your chances of getting lucrative employment in the field.

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Big Data

Teen banking app Step reaches for the stars to raise $50 million




By Anna Irrera

LONDON (Reuters) – Teen banking app Step has raised $50 million (37.4 million pounds) from investors led by Coatue Management alongside celebrities such as singer Justin Timberlake, influencer Charli D’Amelio and former quarterback Eli Manning.

Step, which offers teenagers a bank account connected to a secured spending card and peer-to-peer payments, also said it had secured funding from existing backers including Stripe, Will Smith’s Dreamers VC, CrossLink Capital and Collaborative Fund.

San Francisco-based Step allows parents to view balances and real-time activity, add money to their teens’ accounts and manage and freeze cards. It does not charge fees but makes money from card interchange.

Other stars involved in the fundraising included The Chainsmokers, Kelvin Beachum, Larry Fitzgerald and Andre Iguodala, Step said in a statement on Wednesday.

The startup, which has attracted more than 500,000 users since launching two months ago, will use the funding to grow the team and invest in its technology, its chief executive CJ MacDonald told Reuters in a video call.

“We are making sure we are building scalable solutions and are able to handle the growth,” MacDonald said.

Step is one of several new banking apps focused on children and teens in the U.S., as companies seek to capitalise on a global surge in digital payments and ecommerce. It rivals products from companies including Greenlight, Copper and JPMorgan Chase & Co.

Such companies say they aim to make it easier for parents and their children to transact in an increasingly cashless economy, while providing more modern financial education tools.

“As a person who hasn’t always had financial stability, and made many mistakes in that arena as a young man, I know the importance of financial education and having access to economic platforms that can work for everyone,” Smith, who is a co-founder of Dreamers VC, said in a statement.

(Reporting by Anna Irrera; Editing by Alexander Smith)

Image Credit: Reuters


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Big Data

Intel’s Habana starts to chip away at Nvidia in cloud with AWS deal




By Steven Scheer

JERUSALEM (Reuters) – Intel Corp’s Habana Labs business said on Wednesday it would take time to gain market share from Nvidia in cloud and data centre computing but its deal this week with Amazon Web Services (AWS) was a solid first step.

Intel in December bought Israel-based artificial intelligence firm Habana for about $2 billion, seeking to expand its AI portfolio to bolster its data-centre business.

Habana’s Gaudi AI training processor, launched in June 2019, has faster processing speeds to compete with similar products from Intel rival Nvidia.

“We have to realise that we’re starting from zero and Nvidia is 100%,” said Eitan Medina, Habana’s chief business officer, who said that having AWS as its first customer was very important.

“The uphill battle or the process of taking market share has to go through convincing end developers to try it out,” he told reporters. “We are making the dent at the most important place. We’re starting with a very big guy that has the longest experience … It will take time but I believe we’re on the right path.”

Medina declined to comment on whether Habana was negotiating other deals.

Habana on Tuesday said its Gaudi processors will power AWS’s Amazon Elastic Compute Cloud “instances” for machine learning workloads, in Habana’s first deal for its Gaudi chips.

Amazon is seeing growing demand for its cloud tools during the coronavirus pandemic. These chips, Intel said, would give 40% better price performance than current graphics processing.

Medina said that the advantages of Gaudi AI chips were efficiency and allowing for lower capital and operating expenses that in turn could give AWS and others the ability to lower prices for customers for server time.

“We are now starting so it will depend on the combination of how we will execute and how important is it for users to lower their cost and to have alternatives to GPUs (graphics processing units),” Medina said. “Our total available market is 100% of AI.”

(Reporting by Steven Scheer. Editing by Jane Merriman)

Image Credit: Reuters


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Big Data

U.S judge hearing Google case rejects government’s protective order request




WASHINGTON (Reuters) – The federal judge hearing the U.S. Justice Department’s antitrust lawsuit against Alphabet’s Google urged the government on Wednesday to narrow the definition of “highly sensitive” information as he considered arguments on which of Google’s lawyers would be able to see evidence produced by other companies.

U.S. District Judge Amit Mehta asked the two sides to produce a revised protective order by Dec. 14 while companies, like Apple Inc or AT&T Inc, which produced the information, would have until Dec. 15 to file on the matter.

The Justice Department, which sued the search and advertising giant in October, put at the core of its antitrust case the billions of dollars that Google paid to be the default search engine on Apple’s iPhones. Apple noted in its filing that sensitive data was used to write the complaint.

(Reporting by Diane Bartz; editing by Jonathan Oatis)

Image Credit: Reuters


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