iOS App Dev

iOS App Dev

1625126457

5 Reasons to Hire Data Scientists for Your Business

We’re living in a data-driven world. All the more reason for companies to hire data scientists to work on a variety of issues.

One of the most popular terms these days is data scientist. Although the word has recently become a great buzzword in the industry, the area of data science isn’t unique. Lots of data scientists have been operating in various industries for quite some experience now.

The purpose of building machines as intelligent as human beings has also been attempted for some time now. Therefore, why is the word appearing in a lot of advertising these days? To explain the appearance, let’s probe deeper into what a data scientist is, take a glance at the attributes that one wants to control to work in this domain, and examine why it has become necessary for companies to hire these professionals.

Data scientists typically have expertise in a few main areas, including machine learning, mathematics, or statistics, software engineering/coding, and expertise in the business in which they explore employment. Most experienced data scientists are influential professions in a broad variety of fields. They often contribute to software development, act as a classical statistician or researcher, or engage in data pipelines and business intelligence roles. Someone with extended experiences in all three areas is an exceptional person and authority. In addition to these abilities, a reliable data science applicant should understand scientific research methods and solid conversation talents to turn results into viable business solutions.

#analytics #big data #big data architectures #data science #data scientist #data scientists

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5 Reasons to Hire Data Scientists for Your Business

Nora Joy

1604154273

Hire Dedicated Data Scientists in India | DxMinds

Hire dedicated data scientist in India ,DxMinds Technologies is the best product engineering company in India making innovative solutions using Machine learning and deep learning. We are among the best to hire data scientist in India work in different industry domains like Healthcare retail, banking and finance ,oil and gas, ecommerce, telecommunication ,FMCG, fashion etc.
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 iOS App Dev

iOS App Dev

1625126457

5 Reasons to Hire Data Scientists for Your Business

We’re living in a data-driven world. All the more reason for companies to hire data scientists to work on a variety of issues.

One of the most popular terms these days is data scientist. Although the word has recently become a great buzzword in the industry, the area of data science isn’t unique. Lots of data scientists have been operating in various industries for quite some experience now.

The purpose of building machines as intelligent as human beings has also been attempted for some time now. Therefore, why is the word appearing in a lot of advertising these days? To explain the appearance, let’s probe deeper into what a data scientist is, take a glance at the attributes that one wants to control to work in this domain, and examine why it has become necessary for companies to hire these professionals.

Data scientists typically have expertise in a few main areas, including machine learning, mathematics, or statistics, software engineering/coding, and expertise in the business in which they explore employment. Most experienced data scientists are influential professions in a broad variety of fields. They often contribute to software development, act as a classical statistician or researcher, or engage in data pipelines and business intelligence roles. Someone with extended experiences in all three areas is an exceptional person and authority. In addition to these abilities, a reliable data science applicant should understand scientific research methods and solid conversation talents to turn results into viable business solutions.

#analytics #big data #big data architectures #data science #data scientist #data scientists

 iOS App Dev

iOS App Dev

1620466520

Your Data Architecture: Simple Best Practices for Your Data Strategy

If you accumulate data on which you base your decision-making as an organization, you should probably think about your data architecture and possible best practices.

If you accumulate data on which you base your decision-making as an organization, you most probably need to think about your data architecture and consider possible best practices. Gaining a competitive edge, remaining customer-centric to the greatest extent possible, and streamlining processes to get on-the-button outcomes can all be traced back to an organization’s capacity to build a future-ready data architecture.

In what follows, we offer a short overview of the overarching capabilities of data architecture. These include user-centricity, elasticity, robustness, and the capacity to ensure the seamless flow of data at all times. Added to these are automation enablement, plus security and data governance considerations. These points from our checklist for what we perceive to be an anticipatory analytics ecosystem.

#big data #data science #big data analytics #data analysis #data architecture #data transformation #data platform #data strategy #cloud data platform #data acquisition

What Is The Hiring Process For Data Scientists At Genpact

With a surge in AI and ML applications to improve business process efficiencies, there has been an increase in data science hiring across companies. It is one of the fastest-growing areas and often requires a robust hiring process to get the best candidates in the team. We got in touch with Sreekanth Menon, VP, Data Science at Genpact to understand their data science hiring process. Sreekanth shares that not only their hiring mechanism looks for the best available candidate but also retains them by providing opportunities to improve their skills over time.

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Gerhard  Brink

Gerhard Brink

1620629020

Getting Started With Data Lakes

Frameworks for Efficient Enterprise Analytics

The opportunities big data offers also come with very real challenges that many organizations are facing today. Often, it’s finding the most cost-effective, scalable way to store and process boundless volumes of data in multiple formats that come from a growing number of sources. Then organizations need the analytical capabilities and flexibility to turn this data into insights that can meet their specific business objectives.

This Refcard dives into how a data lake helps tackle these challenges at both ends — from its enhanced architecture that’s designed for efficient data ingestion, storage, and management to its advanced analytics functionality and performance flexibility. You’ll also explore key benefits and common use cases.

Introduction

As technology continues to evolve with new data sources, such as IoT sensors and social media churning out large volumes of data, there has never been a better time to discuss the possibilities and challenges of managing such data for varying analytical insights. In this Refcard, we dig deep into how data lakes solve the problem of storing and processing enormous amounts of data. While doing so, we also explore the benefits of data lakes, their use cases, and how they differ from data warehouses (DWHs).


This is a preview of the Getting Started With Data Lakes Refcard. To read the entire Refcard, please download the PDF from the link above.

#big data #data analytics #data analysis #business analytics #data warehouse #data storage #data lake #data lake architecture #data lake governance #data lake management