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In the past year, the Covid-19 pandemic has accelerated the shift to digital health and drove unprecedented investments in the health tech space. The healthcare data analytics companies have gathered a substantial volume of the amount in the first quarter of 2023. Some analysts predicted that the pandemic inspired a decline in investments, but 2023 has proven to be a successful year for big venture investments and is breaking all records. Analytics Insight presents the top digital health data analytics funding that took place in 2023.• Komodo Health
Amount Raised: US$220M Transaction Type: Series E Key Investor(s): Tiger Global Management, Casdin Capital, and others Komodo Health is an AI-enabled data analytics software platform for healthcare providers. It brings transparency and market intelligence to healthcare and life sciences. The software platform applies AI and other disruptive technologies to its healthcare map.• Ro
Amount Raised: US$500M Transaction Type: Series D Key Investor(s): General Catalyst, TQ Ventures, and others Ro is a New-York based startup that includes online pharmacy services, telehealth, and in-home care. It is a telehealth company with three online health clinics, and currently, it is focusing on expanding into remote monitoring for chronic conditions.• Evidation Health
Amount Raised: US$153M Transaction Type: Series E Key Investor(s): OMERS Growth Equity, and others It is a health data analytics company that aims to empower its users to participate in better health outcomes. Evidation measures health in everyday life and enables anyone to participate in its groundbreaking research and health programs.• Innovaccer
Amount Raised: US$105M Transaction Type: Series D Key Investor(s): Tiger Global Management, and others
In the past year, the Covid-19 pandemic has accelerated the shift to digital health and drove unprecedented investments in the health tech space. The healthcare data analytics companies have gathered a substantial volume of the amount in the first quarter of 2023. Some analysts predicted that the pandemic inspired a decline in investments, but 2023 has proven to be a successful year for big venture investments and is breaking all records. Analytics Insight presents the top digital health data analytics funding that took place in 2023.Amount Raised: US$220M Transaction Type: Series E Key Investor(s): Tiger Global Management, Casdin Capital, and others Komodo Health is an AI-enabled data analytics software platform for healthcare providers. It brings transparency and market intelligence to healthcare and life sciences. The software platform applies AI and other disruptive technologies to its healthcare map.Amount Raised: US$500M Transaction Type: Series D Key Investor(s): General Catalyst, TQ Ventures, and others Ro is a New-York based startup that includes online pharmacy services, telehealth, and in-home care. It is a telehealth company with three online health clinics, and currently, it is focusing on expanding into remote monitoring for chronic conditions.Amount Raised: US$153M Transaction Type: Series E Key Investor(s): OMERS Growth Equity, and others It is a health data analytics company that aims to empower its users to participate in better health outcomes. Evidation measures health in everyday life and enables anyone to participate in its groundbreaking research and health programs.Amount Raised: US$105M Transaction Type: Series D Key Investor(s): Tiger Global Management, and others Innovaccer is a healthcare data startup. It delivers healthcare through pioneering analytics and transparent data. It aims to fully use the data that the industry collects and transform care delivery to work as one.
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2023 wasn’t a comfortable year for business. Companies worldwide switched to remote working and had to adapt to the new (online) environment. With this transition came an increase in cybercrime issues and data breaches.
In the first half of 2023, data breaches exposed 36 billion records. And 58% of them involved the personal data of users. The number of phishing attacks went up too –one in every 4,200 emails was a scam.Top 7 Privacy Trends for Companies to Look Out for in 2023
When updating to a hosted dedicated host, it’s crucial to keep in mind that not all the dedicated servers are the same and neither would be the hosting solutions provided by service suppliers. Since it can be tricky to be aware of the essential qualities to search for when locating a supplier, we have assembled this listing of those we believe are the most crucial. They will provide you much clearer insight into what to search for.1. The Year of Privacy Laws
General Data Protection Regulation, or GDPR, put into action in 2023, was one of the first and landmark laws focused on consumers’ digital privacy rights.
It obliged companies that gather and utilize people’s information to record data breaches and gave consumers more rights to restrain the organization’s data on them, e.g., to need to delete their information (“the right to be forgotten”). California implemented an identical judgment (CCPA) in June 2023.
In 2023 India’s solitude dictates will probably become legislation, and more nations will follow. Based on Gartner, 65 percent of the planet’s inhabitants will have their information covered under privacy legislation by 2023.2. App Tracking Policies Developed
Also read: Top 9 WordPress Lead Generation Plugins in 20233. There Will Be a Further Increase in Data Breaches
In 2023, you will find 331 data breach alarms every day across Europe, a 19% growth since 2023. Researchers anticipate the number of data breaches to leap up much more in 2023. The insider threat will rise, Forrester forecasts the share of information breaches brought on by insiders increases to 33 percent in 2023.
Now 45 percent of all Americans are more concerned about their online privacy than they were a year ago. To protect themselves from information breaches, in 2023 users will further adopt applications that help them protect their private information.
By way of instance, in 2023, Virtual Private Network (VPN) use jumped by 27.1percent, and that season the number of people who use VPNs will keep growing.4. Companies will Further Implement User Data Privacy Automation
GDPR provides users the right to request a company to reveal all of the information they gathered. And, if the user needs it, the corporation is going to need to delete it entirely. To deal with these requests, businesses introduce solitude automation features that’ll automatically collect, put together and present the information to the consumer.
Additionally, these attributes will delete all of the information if necessary. Businesses might develop them look for outsourcing or B2B solutions.
Primarily, an individual needs to get in touch with our service with a need to present their information or delete it.
Our engineers run a unique script that hunts for all of the information which may be associated with the user. Following the script finds that the information, can either delete it or set in a distinctive mobile record, which we will send to the consumer.5. Cybersecurity Focus Due to Increased Cloud Adoption
At precisely the same time, external strikes on cloud balances increased by 630 percent. These strikes affected authorities, manufacturing, and transport the most. At the start of this calendar year, experts discovered malware that targeted Apple’s latest M1 chip.
In 2023 cybersecurity will turn into one of the primary centers of companies, particularly small and mid-century ones. Businesses want to apply new tools and practices to safeguard their remote workspaces.
By way of instance, employ secure gateways for their cloud solutions by allowing access to them just using the company VPN. They’ll also present multi-factor authentication (MFA) when they have not already to prevent compromised workers’ credentials used by hackers.
Even though the clinic is very popular with large IT companies, less than a third of workers used this kind of authentication in smaller businesses in 2023.
Also read: Top 9 WordPress Lead Generation Plugins in 20236. Companies will Adopt Zero-Trust Architecture
Normally, businesses stored their information on-premise servers, and any work that had been present at work had access to them. The bodily Security Perimeter shielded the business enterprise.
However, with much more workers working remotely, some as salespeople, and much more valuable information being saved on the cloud, even the security of their Security Perimeter is suspicious, and lots of defense holes bugs can exploit look. That is when a zero-trust structure gets beneficial.
To perform it, businesses can use bespoke enterprise applications or construct their very own Single Sign-On (SSO) servers. MacPaw, by way of instance, utilizes a centralized SSO way to check the identity of the group members.7. Consumer Privacy to Become a Competitive Advantage
Based on Cisco, 84 percent of consumers care about the privacy of the information. More than 50 percent of these will change companies due to their data policies or information-sharing practices. In 2023 companies (particularly those working primarily on the internet ) will have to admit their customers care about solitude. If their customers are not happy with the way the provider handles their information, they’ll go to rivals with better privacy policies.
As soon as we develop our services and products, we ensure that they comply with all the conventional privacy regulations and manage privacy-based requests expeditiously. In 2023 we found ClearVPN — a fresh approach to VPN-based solutions for routine users.To Sum It Up
PGDM big data analytics is thriving in educational institutes for this data-driven world
A PGDM course is one of the necessary educational certificates to get recruited by multiple hi-tech companies. It can help to earn good salaries with different focused professional paths such as artificial intelligenceTop ten PGDM big data analytics courses in 2023 PGDM Big Data Analytics at Fore School of Management
The objective is to familiarize the students with data management, big data, data analytics, and insights to help in decision-making in multiple data-driven industries. The PGDM course will also help to develop a conceptual framework for analytical models and strategies while improving the business.PGDM Big Data Analytics at Institute of Digital Technology Management
Students tend to gain exposure to multiple independent projects, role plays, simulations, presentations, seminars, and industry-based projects for four months. The course on big data includes core courses in big data analytics, hands-on experience with cutting-edge technologies, and the confidence to face real-life problems efficiently.PGDM Big Data Analytics at Goa Institute of Management
The PGDM course covers the examination of large and varied data sets to discover hidden patterns, unknown correlations, market trends, and many more powerful data and insights in the real world. There are case-based learning, simulations, seminars, assignments, and many on-site industry projects in this PGDM course.Executive PGDM Big Data Analytics at IFIM Business School
The big data course is 15-month long for working executives to gain knowledge of big data analytics with a professional certificate. The course on big data covers both relevant theoretical and practical knowledge to provide effective solutions to real-life situations. There are multiple areas of specialization in industry-based projects.PGD in Business Analytics at IIM Calcutta, IIT Kharagpur, and ISI
The mission of this business analytics and big data analytics course is to shape the emerging profession with interdisciplinary educational experience. The course includes marketing management, managerial communication, regression and time series models, modeling in operations management, and many more.PGDM in Data Science, Business Analytics, and Big Data at Aegis School of Business
This course is well-known for providing in-depth knowledge of simulating fields of big data analytics, business analytics, and data science. It is the first data science program designed with IBM in India.PGDM Big Data Analytics at IMS Ghaziabad
This big data course is one of the top PGDM big data analytics courses in India for aspiring techies in the global tech market. The curriculum covers the in-depth knowledge of big data analytics, data science, and many more with hands-on experiences through projects and assignments.PGDM in Big Data Analytics at Sunbeam PGDM in Big Data Analytics and Business Analytics at Srinivas University
This course is known for covering business-related tools and allowing data-driven decision-making in businesses. The students will gain extensive knowledge of statistics with quantitative skills and risk management.PGDM in Research and Business Analytics at IBMR
This course is focused on providing students with flexibility in business analytics with business knowledge, practical experiences, and training skills. It includes sufficient coverage of important topics and areas of business analytics and big data analytics to flourish in real-life companies across the world.
Data analytics is the systematic analysis of data to discover and interpret useful patterns and trends in data.
The digital transformations occurring at companies and related data-driven products and services come with the need to analyze and make use of all the resulting business data. Companies, regardless of industry, are adding data analysts to their data science teams.
When looking for companies hiring for data analytics jobs, it’s important to find an employer with a employee-oriented work culture. See below to learn about 10 of the top companies looking to fill jobs related to data analytics, their culture, and benefits:
See more: The Data Analytics Job Market
ScienceSoft is a provider of IT consulting services, such as data analytics for financial, customer, supply chain, and product analytics.
At ScienceSoft, you can work as a:
Middle business analyst
Junior market analyst
UX business analyst
With an emphasis on work-life balance, the ScienceSoft workplace nurtures cooperation among employees.
Employment benefits at ScienceSoft include:
PTO and parental leave
Flexible work from home policy
At Beyond the Arc, you can work as a:
Data analytics intern
Business analyst and consultant
Marketing strategist and analyst
Beyond the Arc’s team of strategists, technicians, and creative professionals are highly collaborative and focus on creating a fun and innovative work environment.
Employment benefits at Beyond the Arc include:
SG Analytics is a global insights and analytics company that offers data-centric research and contextual analytics services.
At SG Analytics, you can work as a:
Senior analyst, financial modeling
Lead analyst, equity research
Operating in over 10 countries, SG Analytics’ strong point is in its diverse and committed talent pool. Employees are encouraged to become leaders and challenge the status quo with accountability, ownership, and spiritedness at the core.
Employment benefits at SG Analytics include:
Remote work available
iTechArt is a software development company and provider of IT and consulting services ranging from real-time data analysis and predictive analytics to behavioral analytics.
At iTechArt, you can work as a:
Senior business intelligence analyst
Information technology analyst
The company culture at iTechArt is firmly rooted in diversity, growth, and giving back to hardworking employees.
Employment benefits at iTechArt include:
PTO and parental leave
Flexible schedules and work-from-home options
Free lunch and snacks
Tableau is a self-service analytics platform and a Salesforce company that helps companies understand data.
At Tableau, you can work as a:
Senior marketing analyst
Senior data analyst
Tableau prides itself on having a supportive community, where data lovers are encouraged to share, learn, and inspire.
Employment benefits at Tableau include:
PTO and parental leave
See more: 5 Top Trends in the Data Analytics Job Market
Qlik is a software-as-a-service (SaaS) company and active intelligence platform that delivers end-to-end, real-time data integration and analytics cloud solutions.
At Qlik, you can work as a:
Onboarding and adoption data analyst/administrator
Analytics data architect
The workspace culture at Qlik is vibrant and cooperative. It promotes fast work, responsibility, an open attitude, and straightforwardness toward teamwork and results.
Employment benefits at Qlik include:
Flexible hours and work from home
Free lunch and snacks
Sisense is an artificial intelligence (AI)-driven platform that enables businesses to drive better and faster decisions for their business and customers using data analytics.
At Sisense, you can work as a:
Sales operations/Deal desk analyst
Global business systems analyst
Business intelligence (BI) analyst
Employees at Sisense are part of a community that thrives on collaboration and doing things “the Sisense way.” Sisense workplace is a diverse environment that welcomes newcomers and guides a path into the future.
Employment benefits at Sisense include:
PTO and parental leave
Free lunch and snacks
TIBCO is a software company that provides real-time data analytics for faster and smarter decisions.
TIBCO is built by its passionate and driven employees. It aims to elevate the customer experience (CX) by first providing employees with a drive for success and a passion for problem solving.
At TIBCO, you can work as a:
Customer retention analyst
Associate HR analyst
Employment benefits at TIBCO include:
Employment stock purchase plan
Work from home and parental leave
MicroStrategy is an enterprise analytics and mobility software company. It provides companies with products and service for data and business analytics.
At MicroStrategy, you can work as a:
At MicroStrategy, employees take pride in their work. They collaborate and share intelligence, while also embracing change and future innovation.
Employment benefits at MicroStrategy include:
Flexible hours and work from home available
Access to LinkedIn Learning
Access to gyms and gym discounts
ThoughtSpot is a cloud-based data analytics company that leverages natural language search and AI in finding data insights.
At ThoughtSpot, you can work as a:
Senior business systems analyst
ThoughtSpot’s workplace is built on selfless excellence. It aims to build a diverse and inclusive team that’s passionate about doing the right thing and making the world a better place.
Employment benefits at ThoughtSpot include:
Work from home and flexible hours
PTO and parental leave
Free lunch and snacks
Mobile phone discount
See more: Top Data Analytics Certifications
Big Data just keeps getting bigger, in a popularity sense. A new IDC report predicts that the Big Data and business analytics market will grow to $203 billion by 2023, double the $112 billion in 2023.
The banking industry is projected to lead the drive and spend the most, which is not surprising, while IT and businesses services will lead most of the tech investing. Overall, IDC finds that the banking, discrete manufacturing, process manufacturing, federal/central government, and professional services will account for about 50% of the overall spending.
Not surprisingly, some of the biggest big data analytics spending — about $60 billion — will go toward reporting and analysis tools. That’s what analytics is all about, after all. Hardware investment will reach nearly $30 billion by 2023.
So as Big Data grows, what will be the major trends? In talking to experts and surveying the research reports, a few patterns emerged.
2) Machine Learning: Big Data solutions will increasingly rely on automated analysis using machine learning techniques like pattern identification and anomaly detection to sort through the vast quantities of data.
3) Predictive analytics: Machine learning is not just for historical analysis, but also can be used to predict future data points. That will start with basic ‘straight-line’ prediction, deducing B from A. But it will eventually grow and become more sophisticated by detecting patterns and anomalies that are about to happen too.
4) Security analytics: To some degree this aready has a significant prescence. Security software, especially intrusion detection, has learned to spot suspicious and anomalous behavior. Big Data, with all of its source inputs, needs to be secured and there will be greater emphasis on securing the data itself. The same processing power and software analytics used to analyze the data will also be used for rapid detection and adaptive responses.
5) The bar is raised: Traditional programmers will have to add gain data science skills to their repertory in order to stay relevant and employable. But just like many programmers are self-taught, there will be a rise in data scientists from nontraditional professional backgrounds, including self-taught data scientists.
6) The old guard fades: A 2023 report from Gartner found Hadoop was fading in popularity in favor of real-time analytics like Apache Spark. Hadoop was, after all, a batch process run overnight. People want answers in real time. So Hadoop, MapReduce, HBase and HDFS are all going to continue to fade in favor of faster technologies.
7) No more hype: Big Data has faded as a buzzword and is now just another technology like RDBMS and CRM. That means the technology has settled into the enterprise as another tool brought to bear. It’s now a maturing product, free of the hype that can be distracting.
8) More Data Scientists: The Data Scientist is probably the most in-demand technologist out there, with people who qualify commanding a significant salary. Nature abhors a vacuum and you will see more people trying to gain Data Scientist skills. Some will go the self-taught route, which is how many programmers acquired their skills in the first place, while others will get training via crowdsourcing.
9) IoT + BD = soulmates: millions of Internet-connected devices, from wearables to factory equipment, will generate massive amounts of data. This will lead to all kinds of feedback, like machine performance, which in turn will lead to optimized performance and earlier warnings before failure, reducing downtime and expenses.
10) The lake gains power: Data lakes, massive repositories of information, have been around for a while but mostly it’s just a store with little idea how to use it. But as organizations demand quicker answers, they will turn to the data lake for those answers.
11) Real time is hot: In a survey of data architects, IT managers, and BI analysts, nearly 70% of the respondents favored Spark over MapReduce. The reason is clear: Spark is in-memory, real time stream processing while MapReduce is batch processing usually done overnight or during off-peak hours. Real-time is in, hours-old data is out.
12) Metadata catalogs: You can gather a lot of data with Hadoop but you can’t always process it, or even find what you need in all that information. Enter Metadata Catalogs, a simple concept where aspects of Big Data analytics, like data quality and security, are stored in a catalog. They catalog files using tags, uncover relationships between data assets, and even provide query suggestions. There are a number of companies offering data cataloging software for Hadoop, plus there is an open source project, Apache Atlas.
13) AI explodes: Artificial intelligence, and its cousin machine learning, will see tremendous growth because there is simply too much data coming in to be analyzed to wait for human eyes. More must be automated for faster responses. This is especially true with the massive amounts of data generated by IoT devices.
14) Dashboard maturity: With Big Data still in its early years, there are a lot of technologies that have yet to mature. You just can’t rush some things. One of them is the right tools to easily translate the data into something useful. Analysts predict that dashboards will finally get some attention from startups like DataHero, Domo, and Looker, among others, that will offer more powerful tools of analysis.
15) Privacy clash: With all the data being gathered, some governments may put the brakes on things for a variety of reasons. There have been numerous government agency hacks and questions about the 2023 Presidential election. This may result on restrictions from the government on how data is gathered and used. Plus, the EU has set some tough new privacy laws regarding how data is used and how models are built, set to take effect in January 2023. The impact is not yet known, but in the future, data might be harder to come by or use.
16) Digital assistants: Digital voice assistants like Amazon Echo and Alexa and Google Home and Chromecast will be the next generation of data gathering, along with Apple Siri and Microsoft Cortana. Don’t think they won’t. These are “always listening” devices used to help people make purchase and other consumption decisions. They will become a data source at least for their providers.
17) In-memory everything: Memory has up to now been relatively cheap, and since 64-bit processors can access up to 16 exabytes of memory, server vendors are cramming as much DRAM into these things as possible. Whether in the cloud or on-premises, memory footprints are exploding, and that’s making way for more real-time analytics like Spark. Working in memory is at three orders of magnitude faster than going to disk and everyone wants more speed.
Analytics Insight has churned out the top Data Science jobs in Gurgaon available in 2023 Data Scientist at Airtel
Airtel is known as one of the largest telecom service providers for customers and businesses in India. It also operates in 18 countries with products such as 2G, 3G and 4G wireless services, high-speed home broadband as well as DTH. The company consists of more than 403 million customers across the world. Responsibilities: The data scientist needs to research, design, implement as well as evaluate novel Computer Vision algorithms, work on large-scale datasets and create scalable systems in versatile application fields. The candidate is required to work closely with the customer expertise team, research scientist teams as well as product engineering teams to drive model implementations along with new algorithms. The candidate also needs to interact with the customer to gain a better understanding of the business problems and help them by implementing machine learning solutions. Qualifications: A candidate is required to have practical experience in Computer Vision and more than three years in building production-scale systems in either Computer Vision, deep learning or machine learning. There should be coding skills in one programming language and a clear understanding of deep learning CV evaluation metrics such as mAP, F_beta and PR curves as well as face detection, facial recognition and OCR. The candidate also needs to have 2-3 years of modelling experience working with Pytorch, MxNet and Tensorflow along with object detection approaches such as Faster RCNN, YOLO and CenterNet.Data Scientist at BluSmart
BluSmart is known as the first and leading all-electric ride-hailing mobility service in India. It has a mission to steer urban India towards a sustainable means of transportation by building a comprehensive electric on-demand mobility platform with smart charging and smart parking. The company will provide efficient, affordable, intelligent as well as reliable mobility. Responsibilities: The candidate is required to do a geospatial and time-based analysis of business vectors like time-travelled, fare, trip start and many more to optimise fleet utilisation and deployment as well as develop strategies to deploy electric vehicles and chargers in Delhi-NCR along with Mumbai by using data from thousands of trip from BluSmart cabs. The data scientist will create a new experimental framework to collect data and build tools to automate data collection by using open-source data analysis and visualisation tools. Qualifications: The candidate is required to have sufficient knowledge of data analytics, machine learning, and programming languages such as R, SQL and Python. The candidate needs to have practical experience with data analytics, machine learning and business intelligence tools such as Tableau with smart mathematical skills.Associate Data Scientist at Pee Safe
Responsibilities: The data scientist should receive actionable insights from data to be used in real-time in all decision-making processes for the company and implement multiple processes across different departments to enhance business metrics. The candidate needs to create new models or improve existing models to be used for the supply chain, demand predictions, logistics and many more. Qualifications: The candidate should have a Bachelor’s degree in Statistics, Mathematics, Computer Science, Engineering or any other relevant field. The candidate is required to have at least two to three years of practical experience in quantitative analytics or data modelling. It is essential to have a clear understanding of predictive modelling, machine learning, clustering, classification techniques, algorithms, programming language as well as Big Data frameworks and visualisation tools such as Cassandra, Hadoop, Spark and Tableau. The candidate must have strong problem-solving skills with sufficient knowledge of Excel.Data Scientist at Siemens Limited
Siemens is popularly known as a technology company focused on industry, infrastructure, mobility as well as healthcare. It aims in creating technologies for more resource-efficient factories along with resilient supply chains to transform industries. Responsibilities: The candidate is required to design software solutions supplemented with Artificial Intelligence and machine learning based on the customer requirements within architectural or design guidelines. The candidate also needs to be involved in the coding of features, bug fixing as well as delivering solutions to scripting and quality guidelines. The person is responsible for ensuring integration and submission of solutions into software configuration management system, performing regular technical coordination and timely reporting. Qualifications: The candidate must have a strong knowledge of Data Science, Artificial Intelligence, machine learning, deep learning, exploratory analysis, predictive modelling, prescriptive modelling and Cloud systems with a B.E/B. Tech/ CA/ M. Tech in science background. The candidate should have practical experience in data visualisation tools, statistical computer languages, data architecture and machine learning techniques. It is essential to have a good knowledge of querying SQL, no SQL databases, data mining techniques, AWS services, computing tools as well as end-to-end Data Science pipelines into production.Data Scientist at Mastercard
Mastercard is known as the global technology company in the financial industry, especially payments. It has a mission to connect an inclusive digital economy to benefit everyone by making transactions safe and accessible. It works in more than 210 countries with secure data and networks, innovations and solutions. Qualifications: The candidate should have practical experience in data management, support decks, SQL Server, Microsoft BI Stack, Python, campaign analytics, SSIS, SSAS, SSRS and data visualisation tools. It is essential to have a Bachelor’s or Master’s degree in Computer Science, IT, Engineering, Mathematics, Statistics or any relevant field.
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